Peter Filzmoser

Publikationen

Puchhammer, P., Wilms, I., & Filzmoser, P. (2024, July 29). Robust sparse PCA for spatial data. ICORS meets DSSV 2024, Fairfax, United States of America (the).
| Robust sparse PCA for spatial data at reposiTUm , opens an external URL in a new window
Oguamalam, J., Radojicic, U., & Filzmoser, P. (2024). Robust covariance estimation and functional anomaly detection based on the Minimum Regularized Covariance Trace estimator. In PROGRAM AND ABSTRACTS - Austrian Statistical Days 2024. Austrian Statistical Days 2024, Wien, Austria.
| Robust covariance estimation and functional anomaly detection based on the Minimum Regularized Covariance Trace estimator at reposiTUm , opens an external URL in a new window
Puchhammer, P., Filzmoser, P., & Wilms, I. (2024, April 4). Groupwise sparse PCA for spatial data. Österreichische Statistiktage 2024 (2024, Wien), Wien, Austria.
| Groupwise sparse PCA for spatial data at reposiTUm , opens an external URL in a new window
Puchhammer, P., Kalubowila, C., Braus, L., Pospiech, S., Sarala, P., & Filzmoser, P. (2024). A performance study of local outlier detection methods for mineral exploration with geochemical compositional data. Journal of Geochemical Exploration, 258, Article 107392. https://doi.org/10.1016/j.gexplo.2024.107392, opens an external URL in a new window
| A performance study of local outlier detection methods for mineral exploration with geochemical compositional data at reposiTUm , opens an external URL in a new window
Cappello, C., Piccolotto, N., Mühlmann, C., Bögl, M., Filzmoser, P., Miksch, S., & Nordhausen, K. (2024). Visual Interactive Parameter Selection for Temporal Blind Source Separation. Journal of Data Science, Statistics, and Visualisation, 4(3). https://doi.org/10.52933/jdssv.v4i3.82, opens an external URL in a new window
| Visual Interactive Parameter Selection for Temporal Blind Source Separation at reposiTUm , opens an external URL in a new window

Puchhammer, P., & Filzmoser, P. (2023). Spatially Smoothed Robust Covariance Estimation for Local Outlier Detection. Journal of Computational and Graphical Statistics. https://doi.org/10.1080/10618600.2023.2277875, opens an external URL in a new window
| Spatially Smoothed Robust Covariance Estimation for Local Outlier Detection at reposiTUm , opens an external URL in a new window
Nesrstová, V., Wilms, I., Palarea‐Albaladejo, J., Filzmoser, P., Martín‐Fernández, J. A., Friedecký, D., & Hron, K. (2023). Principal balances of compositional data for regression and classification using partial least squares. Journal of Chemometrics, 37(12), Article e3518. https://doi.org/10.1002/cem.3518, opens an external URL in a new window
| Principal balances of compositional data for regression and classification using partial least squares at reposiTUm , opens an external URL in a new window
Parzer, R., Vana Gür, L., & Filzmoser, P. (2023). Sparse Projected Averaged Regression for High-Dimensional Data. arXiv. https://doi.org/10.34726/5489, opens an external URL in a new window
| Sparse Projected Averaged Regression for High-Dimensional Data at reposiTUm , opens an external URL in a new window
Neubauer, L., & Filzmoser, P. (2023). Improving Forecasts for Heterogeneous Time Series by “Averaging”, with Application to Food Demand Forecast. arXiv. https://doi.org/10.48550/arXiv.2306.07119, opens an external URL in a new window
| Improving Forecasts for Heterogeneous Time Series by "Averaging", with Application to Food Demand Forecast at reposiTUm , opens an external URL in a new window
Filzmoser, P., Mayrhofer, M., Radojicic, U., & Lewitschnig, H. (2023). Explainable outlier identification for matrix-valued observations. In Book of Abstracts : International Conference on Data Science : ICDS 2023 : Multidimensional Perspectives: From Statistical Learning to Data Science Applications (pp. 13–13).
| Explainable outlier identification for matrix-valued observations at reposiTUm , opens an external URL in a new window
Piccolotto, N., Bogl, M., Muehlmann, C., Nordhausen, K., Filzmoser, P., Schmidt, J., & Miksch, S. (2023). Data Type Agnostic Visual Sensitivity Analysis. IEEE Transactions on Visualization and Computer Graphics. https://doi.org/10.1109/TVCG.2023.3327203, opens an external URL in a new window
| Data Type Agnostic Visual Sensitivity Analysis at reposiTUm , opens an external URL in a new window
Rieser, C., & Filzmoser, P. (2023). Extending compositional data analysis from a graph signal processing perspective. Journal of Multivariate Analysis, 198, Article 105209. https://doi.org/10.1016/j.jmva.2023.105209, opens an external URL in a new window
| Extending compositional data analysis from a graph signal processing perspective at reposiTUm , opens an external URL in a new window
Piccolotto, N., Bögl, M., Mühlmann, C., Nordhausen, K., Filzmoser, P., Schmidt, J., & Miksch, S. (2023, October 26). Data Type Agnostic Visual Sensitivity Analysis. IEEE VIS 2023, Melbourne, Australia.
| Data Type Agnostic Visual Sensitivity Analysis at reposiTUm , opens an external URL in a new window
Pfeiffer, P., & Filzmoser, P. (2023). Robust statistical methods for high-dimensional data, with applications in tribology. Analytica Chimica Acta, 1279(341762). https://doi.org/10.34726/5289, opens an external URL in a new window
| Robust statistical methods for high-dimensional data, with applications in tribology at reposiTUm , opens an external URL in a new window
Mayrhofer, M., Lewitschnig, H., & Filzmoser, P. (2023, October 19). New Mission Profile Model Using Functional Data Analysis. Infineon meets University 2023, Germany.
| New Mission Profile Model Using Functional Data Analysis at reposiTUm , opens an external URL in a new window
Rieser, C., Fačevicová, K., & Filzmoser, P. (2023). Cell-wise robust covariance estimation for compositions, with application to geochemical data. Journal of Geochemical Exploration, 253, Article 107299. https://doi.org/10.1016/j.gexplo.2023.107299, opens an external URL in a new window
| Cell-wise robust covariance estimation for compositions, with application to geochemical data at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Mayrhofer, M. (2023). Outlier explanation based on Shapley values for vector- and matrix-valued observations. In P. Coretto, G. N. Giordano, & M. La Rocca (Eds.), CLADAC 2023 : Book of Abstracts and Short Papers : 14th Scientific Meeting of the Classification and Data Analysis Group (pp. 156–158). Pearson Education Resources.
| Outlier explanation based on Shapley values for vector- and matrix-valued observations at reposiTUm , opens an external URL in a new window
Mayrhofer, M., & Filzmoser, P. (2023). Explainable outlier detection based on Shapley values. In PROGRAMME AND ABSTRACTS 25th International Conference on Computational Statistics (COMPSTAT 2023) (pp. 13–14).
| Explainable outlier detection based on Shapley values at reposiTUm , opens an external URL in a new window
Puchhammer, P., & Filzmoser, P. (2023, August 7). Spatial outlier detection using the spatially smoothed MRCD. 22nd Annual Conference of the International Association for Mathematical Geosciences 2023 (IAMG2023), Trondheim, Norway.
| Spatial outlier detection using the spatially smoothed MRCD at reposiTUm , opens an external URL in a new window
Heiler, G., Hanbury, A., & Filzmoser, P. (2023). The Impact of COVID-19 on Relative Changes in Aggregated Mobility Using Mobile-phone Data. Austrian Journal of Statistics, 52(4), 163–179. https://doi.org/10.17713/ajs.v52i4.1510, opens an external URL in a new window
| The Impact of COVID-19 on Relative Changes in Aggregated Mobility Using Mobile-phone Data at reposiTUm , opens an external URL in a new window
Drastichová, M., Filzmoser, P., & Gajanin, R. (2023). Relationships between wellbeing and sustainable development in a group of selected developed countries. Problemy Ekorozwoju, 18(2), 49–77. https://doi.org/10.35784/preko.3941, opens an external URL in a new window
| Relationships between wellbeing and sustainable development in a group of selected developed countries at reposiTUm , opens an external URL in a new window
Neubauer, L., & Filzmoser, P. (2023). A New Look at Model Averaging of Differently Sized Time Series. In DSSV 2023 : Book of Abstracts. DSSV-ECDA 2023, Antwerpen, Belgium.
| A New Look at Model Averaging of Differently Sized Time Series at reposiTUm , opens an external URL in a new window
Mayrhofer, M., Rieser, C., & Filzmoser, P. (2023). L0 Regularized Cellwise Outlier Detection and Covariance Estimation. In Book of abstracts: Joint conference of Data Science, Statistics & Visualisation and the European Conference on Data Analysis (pp. 95–95).
| L0 Regularized Cellwise Outlier Detection and Covariance Estimation at reposiTUm , opens an external URL in a new window
Oguamalam, J., Radojicic, U., & Filzmoser, P. (2023). Functional Outlier Detection based on the Minimum Regularized Covariance Trace Estimator. In Book of abstracts: Joint conference of Data Science, Statistics & Visualisation and the European Conference on Data Analysis (pp. 102–102).
| Functional Outlier Detection based on the Minimum Regularized Covariance Trace Estimator at reposiTUm , opens an external URL in a new window
Parzer, R., Vana Gür, L., & Filzmoser, P. (2023). Combining New Dimension Reduction Tools for High-Dimensional Regression. In DSSV 2023 : Book of Abstracts (pp. 103–103).
| Combining New Dimension Reduction Tools for High-Dimensional Regression at reposiTUm , opens an external URL in a new window
Kurnaz, F. S., & Filzmoser, P. (2023). Robust and sparse multinomial regression in high dimensions. Data Mining and Knowledge Discovery, 37(4), 1609–1629. https://doi.org/10.1007/s10618-023-00936-6, opens an external URL in a new window
| Robust and sparse multinomial regression in high dimensions at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Monti, G. S. (2023, June 12). A robust knockoff filter for sparse regression with microbiome compositions. ODAM 2023, Olomouc, Czechia.
| A robust knockoff filter for sparse regression with microbiome compositions at reposiTUm , opens an external URL in a new window
Mayrhofer, M., & Filzmoser, P. (2023). Explainable Multivariate Outlier Detection based on Shapley Values. In Book of Abstracts Olomoucian Days of Applied Mathematics ODAM 2023 (pp. 53–53).
| Explainable Multivariate Outlier Detection based on Shapley Values at reposiTUm , opens an external URL in a new window
Oguamalam, J., Radojicic, U., & Filzmoser, P. (2023). Minimum Regularized Covariance Trace Estimator and Outlier Detection for Functional Data. In Book of Abstracs - Olomoucian Days of Applied Mathematics ODAM 2023 (pp. 57–57).
| Minimum Regularized Covariance Trace Estimator and Outlier Detection for Functional Data at reposiTUm , opens an external URL in a new window
Puchhammer, P., & Filzmoser, P. (2023, June 12). Detecting Local Outliers Using the Spatially Smoothed MRCD Estimator. Olomoucian Days of Applied Mathematics ODAM 2023, Olomouc, Czechia.
| Detecting Local Outliers Using the Spatially Smoothed MRCD Estimator at reposiTUm , opens an external URL in a new window
Mayrhofer, M., Radojicic, U., Lewitschnig, H., & Filzmoser, P. (2023, May 24). Outlier detection and explanation for matrix-valued data. International Conference on Robust Statistics (ICORS) - 2023, Toulouse, France.
| Outlier detection and explanation for matrix-valued data at reposiTUm , opens an external URL in a new window
Pfeiffer, P., Alfons, A., & Filzmoser, P. (2023, May 24). Robust and Sparse CCA: An Algorithm for Dimension Reduction via Sparsity Inducing Penalties.. International Conference on Robust Statistics (ICORS 2023), Toulouse, France.
| Robust and Sparse CCA: An Algorithm for Dimension Reduction via Sparsity Inducing Penalties. at reposiTUm , opens an external URL in a new window
Puchhammer, P., & Filzmoser, P. (2023). A spatially smoothed MRCD estimator for local outlier detection. In ICORS 2023 - Book of Abstracts (pp. 58–59).
| A spatially smoothed MRCD estimator for local outlier detection at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2023, April 18). Robust Sparse Multinomial Regression. DaSSWeb -- Data Science and Statistics Webinar, Portugal.
| Robust Sparse Multinomial Regression at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2023, April 13). Robust statistical methods applied to high-dimensional data from tribology. ANAKON 2023, Wien, Austria.
| Robust statistical methods applied to high-dimensional data from tribology at reposiTUm , opens an external URL in a new window
Parzer, R., Vana Gür, L., & Filzmoser, P. (2023, March 8). High-dimensional Regression using Screening, Random Projection and Averaging. 16th German Probability and Statistics Days 2023, Essen, Germany.
| High-dimensional Regression using Screening, Random Projection and Averaging at reposiTUm , opens an external URL in a new window
Neubauer, L., & Filzmoser, P. (2023, March 7). Improving Forecasts for Time Series of Different Lengths by “Averaging”, with Application to Food Demand Prediction. 16th German Probability and Statistics Days Essen 2023, Essen, Germany.
| Improving Forecasts for Time Series of Different Lengths by "Averaging", with Application to Food Demand Prediction at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Mazak-Huemer, A. (2023). Massive Data Sets – Is Data Quality Still an Issue? In B. Vogel-Heuser & M. Wimmer (Eds.), Digital Transformation (Vol. 1, pp. 269–279). Springer Vieweg. https://doi.org/10.1007/978-3-662-65004-2_11, opens an external URL in a new window
| Massive Data Sets – Is Data Quality Still an Issue? at reposiTUm , opens an external URL in a new window
Kurnaz, F. S., & Filzmoser, P. (2023). enetLTS: robust and sparse methods for high dimensional linear, binary, and multinomial regression. Journal of Open Source Software, 8(82), Article 4773. https://doi.org/10.21105/joss.04773, opens an external URL in a new window
| enetLTS: robust and sparse methods for high dimensional linear, binary, and multinomial regression at reposiTUm , opens an external URL in a new window

Piccolotto, N., Bögl, M., Gschwandtner, T., Muehlmann, C., Nordhausen, K., Filzmoser, P., & Miksch, S. (2022). TBSSvis: Visual analytics for temporal blind source separation. Visual Informatics, 6(4), 51–66. https://doi.org/10.1016/j.visinf.2022.10.002, opens an external URL in a new window
| TBSSvis: Visual analytics for temporal blind source separation at reposiTUm , opens an external URL in a new window
Mayrhofer, M., & Filzmoser, P. (2022). Multivariate outlier explanations using Shapley values and Mahalanobis distances. arXiv. https://doi.org/10.34726/3163, opens an external URL in a new window
| Multivariate outlier explanations using Shapley values and Mahalanobis distances at reposiTUm , opens an external URL in a new window
Sarala, P., Lunkka, J. P., Sarajärvi, V., Sarala, O., & Filzmoser, P. (2022). Timing of glacial - non-glacial stages in Finland: An exploratory analysis of the OSL data. Arctic, Antarctic, and Alpine Research, 54(1), 428–442. https://doi.org/10.1080/15230430.2022.2117765, opens an external URL in a new window
| Timing of glacial - non-glacial stages in Finland: An exploratory analysis of the OSL data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2022, September 20). Robust linear and logistic regression for high-dimensional compositional data. Applied Statistics 2022, Ljubljana, Slovenia.
| Robust linear and logistic regression for high-dimensional compositional data at reposiTUm , opens an external URL in a new window
Pfeiffer, P., Ronai, B., Vorlaufer, G., Dörr, N., & Filzmoser, P. (2022). Weighted LASSO variable selection for the analysis of FTIR spectra applied to the prediction of engine oil degradation. Chemometrics and Intelligent Laboratory Systems, 228, Article 104617. https://doi.org/10.1016/j.chemolab.2022.104617, opens an external URL in a new window
| Weighted LASSO variable selection for the analysis of FTIR spectra applied to the prediction of engine oil degradation at reposiTUm , opens an external URL in a new window
Pfeiffer, P., Ronai, B., Vorlaufer, G., Dörr, N., & Filzmoser, P. (2022, September 15). Prediction of engine oil degradation based on FTIR spectroscopic data. Symposium 2022 der Österreichischen Tribologischen Gesellschaft (ÖTG), Wr. Neustadt, Austria.
| Prediction of engine oil degradation based on FTIR spectroscopic data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2022, August 31). Benford goes multivariate: A new fraud detection method, with application to music streaming data. Models and Learning in Clustering and Classification, Catania, Italy.
| Benford goes multivariate: A new fraud detection method, with application to music streaming data at reposiTUm , opens an external URL in a new window
Pfeiffer, P., Alfons, A., & Filzmoser, P. (2022, August 24). Efficient computation of robust multivariate maximum association. 24th International Conference on Computational Statistics, Bologna, Italy.
| Efficient computation of robust multivariate maximum association at reposiTUm , opens an external URL in a new window
Monti, G. S., & Filzmoser, P. (2022). A robust knockoff filter for sparse regression analysis of microbiome compositional data. Computational Statistics, 271–288. https://doi.org/10.1007/s00180-022-01268-7, opens an external URL in a new window
| A robust knockoff filter for sparse regression analysis of microbiome compositional data at reposiTUm , opens an external URL in a new window
Fačevicová, K., Filzmoser, P., & Hron, K. (2022). Compositional cubes: a new concept for multi-factorial compositions. Statistical Papers. https://doi.org/10.1007/s00362-022-01350-8, opens an external URL in a new window
| Compositional cubes: a new concept for multi-factorial compositions at reposiTUm , opens an external URL in a new window
Mayrhofer, M., & Filzmoser, P. (2022, July 6). Outlier explanation using Shapley values and Mahalanobis distances. International Conference on Robust Statistics (ICORS 2022), Waterloo, Canada.
| Outlier explanation using Shapley values and Mahalanobis distances at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2022, July 5). Robust multinomial regression in high dimensions. International Conference on Robust Statistics (ICORS 2022), Waterloo, Canada.
| Robust multinomial regression in high dimensions at reposiTUm , opens an external URL in a new window
Pfeiffer, P., Ronai, B., Vorlaufer, G., Dörr, N., & Filzmoser, P. (2022, June 21). Prediction of engine oil degradation based on FTIR spectra and weighted LASSO regression. 5th Young Tribological Researcher Symposium (YTRS), Karlsruhe, Germany.
| Prediction of engine oil degradation based on FTIR spectra and weighted LASSO regression at reposiTUm , opens an external URL in a new window
Piccolotto, N., Bögl, M., Mühlmann, C., Nordhausen, K., Filzmoser, P., & Miksch, S. (2022, June 15). Visual Parameter Selection for Spatial Blind Source Separation. EuroVis 2022, Rome, Italy.
| Visual Parameter Selection for Spatial Blind Source Separation at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2022, June 7). Outliers and compositional data. SEMACRET kick-off meeting, Finland.
| Outliers and compositional data at reposiTUm , opens an external URL in a new window
Weltler, P., Rappersberger, K., Filzmoser, P., & Vujic, I. (2022). The impact of the COVID‐19 pandemic on melanoma diagnoses. JEADV Clinical Practice, 1(2), 122–125. https://doi.org/10.1002/jvc2.15, opens an external URL in a new window
| The impact of the COVID‐19 pandemic on melanoma diagnoses at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2022, May 31). Robust and sparse multinomial regression. Statistics and Econometrics Seminar, Berlin, Germany.
| Robust and sparse multinomial regression at reposiTUm , opens an external URL in a new window
Pfeiffer, P., Ronai, B., Vorlaufer, G., Dörr, N., & Filzmoser, P. (2022, April 28). Weighted LASSO feature selection for the analysis of FT-IR spectra applied to relate engine oil degradation patterns. Tribology International Conference 2022, Barcelona, Spain.
| Weighted LASSO feature selection for the analysis of FT-IR spectra applied to relate engine oil degradation patterns at reposiTUm , opens an external URL in a new window
Pavlu, I., Filzmoser, P., Menafoglio, A., & Hron, K. (2022). Classification of continuous distributional data using the logratio approach. In P. Brito & S. Dias (Eds.), Analysis of Distributional Data (pp. 184–202). https://doi.org/10.1201/9781315370545-9, opens an external URL in a new window
| Classification of continuous distributional data using the logratio approach at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2022, April 7). Statistik basierend auf absoluter bzw. relativer Information. TUforMath, Wien, Austria.
| Statistik basierend auf absoluter bzw. relativer Information at reposiTUm , opens an external URL in a new window
Brandl, M., Hauzenberger, C. A., Filzmoser, P., & Martinez, M. M. (2022). Geochemical sourcing of chipped stone tools from Platia Magoula Zarkou. In E. Alram-Stern, K. Gallis, & G. Toufexis (Eds.), Platia Magoula Zarkou. The Neolithic Period. (Vol. 23, pp. 291–309). Austrian Academy of Sciences Press.
| Geochemical sourcing of chipped stone tools from Platia Magoula Zarkou. at reposiTUm , opens an external URL in a new window
Brandl, M., Hauzenberger, C. A., Filzmoser, P., & Trnka, G. (2022). Swieciechow in the south - geochemical provenance of a “flint” axe from Austria. In M. Grygiel & P. Obst (Eds.), Walking among ancient trees. (pp. 533–546). Fundacja Badan Archeologicnych Imenia Profesora Konrada Jazdzewskiego.
| Swieciechow in the south - geochemical provenance of a "flint" axe from Austria. at reposiTUm , opens an external URL in a new window
Mumic, N., Leodolter, O., Schwaiger, A., & Filzmoser, P. (2022). Scale Invariant and Robust Pattern Identification in Univariate Time Series, with Application to Growth Trend Detection in Music Streaming Data. In A. Steland & K.-L. Tsui (Eds.), Artificial Intelligence, Big Data and Data Science in Statistics (pp. 25–50). Springer Nature, Cham. https://doi.org/10.1007/978-3-031-07155-3_2, opens an external URL in a new window
| Scale Invariant and Robust Pattern Identification in Univariate Time Series, with Application to Growth Trend Detection in Music Streaming Data at reposiTUm , opens an external URL in a new window
Piccolotto, N., Bögl, M., Muehlmann, C., Nordhausen, K., Filzmoser, P., & Miksch, S. (2022). Visual Parameter Selection for Spatial Blind Source Separation. Computer Graphics Forum, 41(3), 157–168. https://doi.org/10.1111/cgf.14530, opens an external URL in a new window
| Visual Parameter Selection for Spatial Blind Source Separation at reposiTUm , opens an external URL in a new window

Mumic, N., & Filzmoser, P. (2021). A multivariate test for detecting fraud based on Benford’s law, with application to music streaming data. Statistical Methods and Applications, 30(3), 819–840. https://doi.org/10.1007/s10260-021-00582-6, opens an external URL in a new window
| A multivariate test for detecting fraud based on Benford's law, with application to music streaming data at reposiTUm , opens an external URL in a new window
Drastichová, M., & Filzmoser, P. (2021). Factors of Quality of Life in a Group of Selected European Union and OECD Countries. Problemy Ekorozwoju, 16(2), 75–93. https://doi.org/10.35784/pe.2021.2.09, opens an external URL in a new window
| Factors of Quality of Life in a Group of Selected European Union and OECD Countries at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2021). A robust method to classify high-dimensional microbiome compositions. 63rd Session of the International Statistical Institute, Den Haag, Netherlands (the).
| A robust method to classify high-dimensional microbiome compositions at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2021). Garbage in - garbage out: Die Auswirkungen der Datenqualität auf Machine Learning. Zukunftsfragen des Baubetriebes, Wien, Austria.
| Garbage in - garbage out: Die Auswirkungen der Datenqualität auf Machine Learning at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2021). Introduction to data analysis techniques and the CODA approach. Short course on Fingerprinting techniques in mineral exploration, Norwegen, Norway.
| Introduction to data analysis techniques and the CODA approach at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2021). Introduction to robust statistics. Data Science Group of VNR Verlag, Deutschland, Germany.
| Introduction to robust statistics at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2021). Relativ versus absolut: Eine Einführung in die Analyse von Kompositionsdaten. AC2T Student Camp, Vorau, Austria.
| Relativ versus absolut: Eine Einführung in die Analyse von Kompositionsdaten at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2021). Robust logistic zero-sum regression for compositional data. Online Conference Data Science, Statistics & Visualization (DSSV) 2021, Rotterdam, Netherlands (the).
| Robust logistic zero-sum regression for compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2021). Robustness aspects for the statistical analysis related to industrial applications. International Conference on Mathematical Methods in Economy and Industry (MMEI), Smolenice, Slovakia.
| Robustness aspects for the statistical analysis related to industrial applications at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2021). Robust Statistics. In B. S. D. Sagar, Q. Cheng, J. McKinley, & F. Agterberg (Eds.), Encyclopedia of Mathematical Geosciences (pp. 1–5). Springer, Cham. https://doi.org/10.1007/978-3-030-26050-7_425-1, opens an external URL in a new window
| Robust Statistics at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Nordhausen, K. (2021). Robust linear regression for high-dimensional data: an overview. Wiley Interdisciplinary Reviews: Computational Statistics. https://doi.org/10.1002/wics.1524, opens an external URL in a new window
| Robust linear regression for high-dimensional data: an overview at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., & Menafoglio, A. (2021). Logratio Approach to Distributional Modeling. In A. Daouia & A. Ruiz-Gazen (Eds.), Advances in Contemporary Statistics and Econometrics (pp. 451–470). Springer, Cham. https://doi.org/10.1007/978-3-030-73249-3_23, opens an external URL in a new window
| Logratio Approach to Distributional Modeling at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., Martin-Fernandez, J. A., & Palarea-Albaladejo, J. (Eds.). (2021). Advances in Compositional Data Analysis. Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-71175-7, opens an external URL in a new window
| Advances in Compositional Data Analysis at reposiTUm , opens an external URL in a new window
Hron, K., Coenders, G., Filzmoser, P., & Palarea-Albaladejo, J. (2021). Analysing Pairwise Logratios Revisited. Mathematical Geosciences, 53(7), 1643–1666. https://doi.org/10.1007/s11004-021-09938-w, opens an external URL in a new window
| Analysing Pairwise Logratios Revisited at reposiTUm , opens an external URL in a new window
Hron, K., Menafoglio, A., Palarea-Albaladejo, J., Filzmoser, P., Talská, R., & Egozcue, J. J. (2021). Weighting of Parts in Compositional Data Analysis: Advances and Applications. Mathematical Geosciences, 54(1), 71–93. https://doi.org/10.1007/s11004-021-09952-y, opens an external URL in a new window
| Weighting of Parts in Compositional Data Analysis: Advances and Applications at reposiTUm , opens an external URL in a new window
Lubbe, S., Filzmoser, P., & Templ, M. (2021). Comparison of Zero Replacement Strategies for Compositional Data with Large Numbers of Zeros. Chemometrics and Intelligent Laboratory Systems, 210(104248), 104248. https://doi.org/10.1016/j.chemolab.2021.104248, opens an external URL in a new window
| Comparison of Zero Replacement Strategies for Compositional Data with Large Numbers of Zeros at reposiTUm , opens an external URL in a new window
Miksova, D., Rieser, C., Filzmoser, P., Middleton, M., & Sutinen, R. (2021). Identification of Mineralization in Geochemistry for Grid Sampling Using Generalized Additive Models. Mathematical Geosciences, 53(8), 1861–1880. https://doi.org/10.1007/s11004-021-09929-x, opens an external URL in a new window
| Identification of Mineralization in Geochemistry for Grid Sampling Using Generalized Additive Models at reposiTUm , opens an external URL in a new window
Mikšová, D., Rieser, C., & Filzmoser, P. (2021). Identification of Mineralization in Geochemistry Along a Transect Based on the Spatial Curvature of Log-Ratios. Mathematical Geosciences, 53(7), 1513–1533. https://doi.org/10.1007/s11004-021-09930-4, opens an external URL in a new window
| Identification of Mineralization in Geochemistry Along a Transect Based on the Spatial Curvature of Log-Ratios at reposiTUm , opens an external URL in a new window
Monti, G. S., & Filzmoser, P. (2021). Robust logistic zero-sum regression for microbiome compositional data. Advances in Data Analysis and Classification, 16(2), 301–324. https://doi.org/10.1007/s11634-021-00465-4, opens an external URL in a new window
| Robust logistic zero-sum regression for microbiome compositional data at reposiTUm , opens an external URL in a new window
Monti, G. S., & Filzmoser, P. (2021). Sparse least trimmed squares regression with compositional covariates for high-dimensional data. Bioinformatics, 37(21), 3805–3814. https://doi.org/10.1093/bioinformatics/btab572, opens an external URL in a new window
| Sparse least trimmed squares regression with compositional covariates for high-dimensional data at reposiTUm , opens an external URL in a new window
Moreau, L., & Filzmoser, P. (2021). Adaptive Trade-offs Towards the Last Glacial Maximum in North-Western Europe: a Multidisciplinary View from Walou Cave. Journal of Paleolithic Archaeology, 4, Article 11. https://doi.org/10.1007/s41982-021-00078-5, opens an external URL in a new window
| Adaptive Trade-offs Towards the Last Glacial Maximum in North-Western Europe: a Multidisciplinary View from Walou Cave at reposiTUm , opens an external URL in a new window
Nordhausen, K., Fischer, G., & Filzmoser, P. (2021). Blind Source Separation for Compositional Time Series. Mathematical Geosciences, 53(5), 905–924. https://doi.org/10.1007/s11004-020-09869-y, opens an external URL in a new window
| Blind Source Separation for Compositional Time Series at reposiTUm , opens an external URL in a new window
Ortner, T., Filzmoser, P., Rohm, M., Brodinova, S., & Breiteneder, C. (2021). Local projections for high-dimensional outlier detection. Metron, 79(2), 189–206. https://doi.org/10.1007/s40300-020-00183-5, opens an external URL in a new window
| Local projections for high-dimensional outlier detection at reposiTUm , opens an external URL in a new window
Pérez-Fernández, S., Martínez-Camblor, P., Filzmoser, P., & Corral, N. (2021). Visualizing the decision rules behind the ROC curves: understanding the classification process. AStA Advances in Statistical Analysis, 105(1), 135–161. https://doi.org/10.1007/s10182-020-00385-2, opens an external URL in a new window
| Visualizing the decision rules behind the ROC curves: understanding the classification process at reposiTUm , opens an external URL in a new window
Rabeder, J., Reitner, H., Wimmer-Frey, I., Filzmoser, P., Mert, M. C., Heinrich, M., Lipiarski, P., Reitner, J. M., Hobinger, G., & Benold, C. (2021). Integrative Analyse der L oss- und L osslehmvorkommen im osterreichischen Alpenvorland und im Wiener Becken { ein Beitrag zum Interaktiven Rohsto -Informationssystem IRIS-Online. BHM Berg- Und Hüttenmännische Monatshefte, 166(4), 206–211. https://doi.org/10.1007/s00501-021-01096-0, opens an external URL in a new window
| Integrative Analyse der L oss- und L osslehmvorkommen im osterreichischen Alpenvorland und im Wiener Becken { ein Beitrag zum Interaktiven Rohsto -Informationssystem IRIS-Online at reposiTUm , opens an external URL in a new window
Rieser, C., & Filzmoser, P. (2021). Multivariate functional outlier detection for compositions. Online Conference Data Science, Statistics & Visualization (DSSV) 2021, Rotterdam, Netherlands (the).
| Multivariate functional outlier detection for compositions at reposiTUm , opens an external URL in a new window
Rieser, C., & Filzmoser, P. (2021). Compositional trend filtering. Annales Mathematicae et Informaticae, 53, 257–270. https://doi.org/10.33039/ami.2021.02.004, opens an external URL in a new window
| Compositional trend filtering at reposiTUm , opens an external URL in a new window
Rieser, C., & Filzmoser, P. (2021). Outlier detection for pandemic-related data using compositional functional data analysis. In M. del C. Boado-Penas, J. Eisenberg, & S. Şahin (Eds.), Springer Actuarial (pp. 251–266). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-030-78334-1_12, opens an external URL in a new window
| Outlier detection for pandemic-related data using compositional functional data analysis at reposiTUm , opens an external URL in a new window
Silva, A., Pedro,Duarte, Brito, P., Filzmoser, P., & Dias, J., G. (2021). MAINT.Data: Modelling and Analysing Interval Data in R. The R Journal, 13(2), 336–364. https://doi.org/10.32614/rj-2021-074, opens an external URL in a new window
| MAINT.Data: Modelling and Analysing Interval Data in R at reposiTUm , opens an external URL in a new window
Templ, M. (2021). Artificial Neural Networks to Impute Rounded Zeros in Compositional Data. In P. Filzmoser, K. Hron, J. A. Martin-Fernandez, & J. Palarea-Albaladejo (Eds.), Advances in Compositional Data Analysis (pp. 163–187). Springer. https://doi.org/10.1007/978-3-030-71175-7_9, opens an external URL in a new window
| Artificial Neural Networks to Impute Rounded Zeros in Compositional Data at reposiTUm , opens an external URL in a new window
Varmuza, K., Dehmer, M., Emmert-Streib, F., & Filzmoser, P. (2021). Automorphism groups of alkane graphs. Croatica Chemica Acta, 94(1). https://doi.org/10.5562/cca3807, opens an external URL in a new window
| Automorphism groups of alkane graphs at reposiTUm , opens an external URL in a new window
de Sousa, J., Hron, K., Fačevicová, K., & Filzmoser, P. (2021). Robust principal component analysis for compositional tables. Journal of Applied Statistics, 48(2), 214–233. https://doi.org/10.1080/02664763.2020.1722078, opens an external URL in a new window
| Robust principal component analysis for compositional tables at reposiTUm , opens an external URL in a new window
de la Rosa de Saa, S., Lubiano, M. A., Sinova, B., Gil, M. Á., & Filzmoser, P. (2021). Location-free robust scale estimates for fuzzy data. IEEE Transactions on Fuzzy Systems, 29(6), 1682–1694. https://doi.org/10.1109/tfuzz.2020.2984203, opens an external URL in a new window
| Location-free robust scale estimates for fuzzy data at reposiTUm , opens an external URL in a new window
Štefelová, N., Alfons, A., Palarea-Albaladejo, J., Filzmoser, P., & Hron, K. (2021). Robust regression with compositional covariates including cellwise outliers. Advances in Data Analysis and Classification, 15(4), 869–909. https://doi.org/10.1007/s11634-021-00436-9, opens an external URL in a new window
| Robust regression with compositional covariates including cellwise outliers at reposiTUm , opens an external URL in a new window

Vencálek, O., Hron, K., & Filzmoser, P. (2020). A comparison of generalised linear models and compositional models for ordered categorical data. Statistical Modelling, 20(3), 249–273. https://doi.org/10.1177/1471082x18816540, opens an external URL in a new window
| A comparison of generalised linear models and compositional models for ordered categorical data at reposiTUm , opens an external URL in a new window
Acitas, S., Filzmoser, P., & Senoglu, B. (2020). A new partial robust adaptive modified maximum likelihood estimator. Chemometrics and Intelligent Laboratory Systems, 204, Article 104068. https://doi.org/10.1016/j.chemolab.2020.104068, opens an external URL in a new window
| A new partial robust adaptive modified maximum likelihood estimator at reposiTUm , opens an external URL in a new window
Acitas, S., Filzmoser, P., & Senoglu, B. (2020). A robust adaptive modified maximum likelihood estimator for the linear regression model. Journal of Statistical Computation and Simulation, 91(7), 1394–1414. https://doi.org/10.1080/00949655.2020.1856847, opens an external URL in a new window
| A robust adaptive modified maximum likelihood estimator for the linear regression model at reposiTUm , opens an external URL in a new window
Drastichova, M., & Filzmoser, P. (2020). The relationship between health outcomes and health expenditure in Europe by using compositional data analysis. Problemy Ekorozwoju, 15(2), 99–110.
| The relationship between health outcomes and health expenditure in Europe by using compositional data analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2020). Statistical data analysis of surface geochemical data including case studies from Finland, Greenland and France. Online-Konferenz, Abschluss-Meeting UpDeep, Espoo, Finland.
| Statistical data analysis of surface geochemical data including case studies from Finland, Greenland and France at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Gregorich, M. (2020). Multivariate outlier detection in applied data analysis: global, local, compositional and cellwise outliers. Mathematical Geosciences, 52(8), 1049–1066. https://doi.org/10.1007/s11004-020-09861-6, opens an external URL in a new window
| Multivariate outlier detection in applied data analysis: global, local, compositional and cellwise outliers at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2020). Compositional Data Analysis in Chemometrics. In R. Tauler, B. Walczak, & S. Brown (Eds.), Comprehensive Chemometrics. Chemical and Biochemical Data Analysis (pp. 641–662). Elsevier. https://doi.org/10.1016/B978-0-12-409547-2.14591-3, opens an external URL in a new window
| Compositional Data Analysis in Chemometrics at reposiTUm , opens an external URL in a new window
Filzmoser, P., Brodinova, S., Ortner, T., Breiteneder, C., & Rohm, M. (2020). Robust and sparse k-means clustering in high dimension. Seminarvortrag an der JKU Linz, Linz, Austria.
| Robust and sparse k-means clustering in high dimension at reposiTUm , opens an external URL in a new window
Filzmoser, P., Höppner, S., Ortner, I., Serneels, S., & Verdonck, T. (2020). Cellwise robust M regression. Computational Statistics & Data Analysis, 147, Article 106944. https://doi.org/10.1016/j.csda.2020.106944, opens an external URL in a new window
| Cellwise robust M regression at reposiTUm , opens an external URL in a new window
Filzmoser, P., Lubbe, S., & Templ, M. (2020). Strategies to replace high proportions of zeros in compositional data. Online Conference - 1st Conference on Information Technology and Data Science, Debrecen, Hungary.
| Strategies to replace high proportions of zeros in compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P., Serneels, S., Maronna, R., & Croux, C. (2020). Robust Multivariate Methods in Chemometrics. In S. Brown, R. Tauler, & B. Walczak (Eds.), Comprehensive Chemometrics: Chemical and Biochemical Data Analysis (pp. 393–430). Elsevier. https://doi.org/10.1016/B978-0-12-409547-2.14642-6, opens an external URL in a new window
| Robust Multivariate Methods in Chemometrics at reposiTUm , opens an external URL in a new window
Heiler, G., Hanbury, A., & Filzmoser, P. (2020). The impact of COVID-19 on relative changes in aggregated mobility using mobile-phone data (p. 14). arXiv. https://doi.org/10.48550/arXiv.2009.03798, opens an external URL in a new window
| The impact of COVID-19 on relative changes in aggregated mobility using mobile-phone data at reposiTUm , opens an external URL in a new window
Hron, K., Engle, M., Filzmoser, P., & Fišerová, E. (2020). Weighted symmetric pivot coordinates for compositional data with geochemical applications. Mathematical Geosciences, 53(4), 655–674. https://doi.org/10.1007/s11004-020-09862-5, opens an external URL in a new window
| Weighted symmetric pivot coordinates for compositional data with geochemical applications at reposiTUm , opens an external URL in a new window
Lemière, B., Melleton, J., Auger, P., Derycke, V., Gloaguen, E., Bouat, L., Mikšová, D., Filzmoser, P., & Middleton, M. (2020). pXRF measurements on soil samples for the exploration of an antimony deposit: example from the Vendean antimony district (France). Minerals, 10(8), Article 724. https://doi.org/10.3390/min10080724, opens an external URL in a new window
| pXRF measurements on soil samples for the exploration of an antimony deposit: example from the Vendean antimony district (France) at reposiTUm , opens an external URL in a new window
Mikšová, D., Filzmoser, P., & Middleton, M. (2020). Imputation of values above an upper detection limit in compositional data. Computers and Geosciences, 136, Article 104383. https://doi.org/10.1016/j.cageo.2019.104383, opens an external URL in a new window
| Imputation of values above an upper detection limit in compositional data at reposiTUm , opens an external URL in a new window
Mikšová, D., Rieser, C., Filzmoser, P., Thaarup, S. M., & Melleton, J. (2020). A method to identify geochemical mineralization on linear transects. Austrian Journal of Statistics, 49(4), 89–98. https://doi.org/10.17713/ajs.v49i4.1133, opens an external URL in a new window
| A method to identify geochemical mineralization on linear transects at reposiTUm , opens an external URL in a new window
Monti, G., & Filzmoser, P. (2020). High-dimensional regression with compositional covariates: a robust perspective. In A. Pollice, N. Salvati, & F. Schirripa Spagnolo (Eds.), Book of Short Papers SIS 2020 (pp. 105–110). Pearson.
| High-dimensional regression with compositional covariates: a robust perspective at reposiTUm , opens an external URL in a new window
Mühlmann, C., Filzmoser, P., & Nordhausen, K. (2020). Local Difference Matrices for Spatial Blind Source Separation. 3rd Conference of the Arabian Journal of Geosciences (CAJG), Tunisia.
| Local Difference Matrices for Spatial Blind Source Separation at reposiTUm , opens an external URL in a new window
Ortner, I., Filzmoser, P., & Croux, C. (2020). Robust and sparse multigroup classification by the optimal scoring approach. Data Mining and Knowledge Discovery, 34(3), 723–741. https://doi.org/10.1007/s10618-019-00666-8, opens an external URL in a new window
| Robust and sparse multigroup classification by the optimal scoring approach at reposiTUm , opens an external URL in a new window
Rieser, C., & Filzmoser, P. (2020). Compositional Trend Filtering. Online Conference - 1st Conference on Information Technology and Data Science, Debrecen, Hungary.
| Compositional Trend Filtering at reposiTUm , opens an external URL in a new window
Rosadi, D., Setiawan, E. P., Templ, M., & Filzmoser, P. (2020). Robust Covariance Estimators for Mean-Variance Portfolio Optimization with Transaction Lots. Operations Research Perspectives, 7, Article 100154. https://doi.org/10.1016/j.orp.2020.100154, opens an external URL in a new window
| Robust Covariance Estimators for Mean-Variance Portfolio Optimization with Transaction Lots at reposiTUm , opens an external URL in a new window
Templ, M., Gussenbauer, J., & Filzmoser, P. (2020). Evaluation of robust outlier detection methods for zero-inflated complex data. Journal of Applied Statistics, 47(7), 1144–1167. https://doi.org/10.1080/02664763.2019.1671961, opens an external URL in a new window
| Evaluation of robust outlier detection methods for zero-inflated complex data at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., Fray, N., Cottin, H., Merouane, S., Stenzel, O., Paquette, J., Kissel, J., Briois, C., Baklouti, D., Bardyn, A., Siljeström, S., Silén, J., & Hilchenbach, M. (2020). Composition of cometary particles collected during two periods of the Rosetta mission: multivariate evaluation of mass spectral data. Journal of Chemometrics, 34(4). https://doi.org/10.1002/cem.3218, opens an external URL in a new window
| Composition of cometary particles collected during two periods of the Rosetta mission: multivariate evaluation of mass spectral data at reposiTUm , opens an external URL in a new window
Varmuza, K., Rados, E., Herzig, C., Limbeck, A., Pittenauer, E., Allmaier, G., & Filzmoser, P. (2020). ICP-MS of meteorite samples: Chemometric evaluation of diversity and discrimination. 31st Mass Spec Forum Vienna, Wien, Austria.
| ICP-MS of meteorite samples: Chemometric evaluation of diversity and discrimination. at reposiTUm , opens an external URL in a new window
van den Boogaart, K. G., Filzmoser, P., Hron, K., Templ, M., & Tolosana-Delgado, R. (2020). Classical and Robust Regression Analysis with Compositional Data. Mathematical Geosciences, 53(5), 823–858. https://doi.org/10.1007/s11004-020-09895-w, opens an external URL in a new window
| Classical and Robust Regression Analysis with Compositional Data at reposiTUm , opens an external URL in a new window

Gozzi, C., Filzmoser, P., Buccianti, A., Vaselli, O., & Nisi, B. (2019). Statistical methods for the geochemical characterisation of surface waters: The case study of the Tiber River basin (Central Italy). Computers and Geosciences, 131, 80–88. https://doi.org/10.1016/j.cageo.2019.06.011, opens an external URL in a new window
| Statistical methods for the geochemical characterisation of surface waters: The case study of the Tiber River basin (Central Italy) at reposiTUm , opens an external URL in a new window
Wurl, A., Falkner, A., Filzmoser, P., Haselböck, A., Mazak, A., & Sperl, S. (2019). A Comprehensive Prediction Approach for Hardware Asset Management. In C. Quix & J. Bernardino (Eds.), Data Management Technologies and Applications (pp. 26–49). Springer Nature Schwitzerland AG 2019. https://doi.org/10.1007/978-3-030-26636-3_2, opens an external URL in a new window
| A Comprehensive Prediction Approach for Hardware Asset Management at reposiTUm , opens an external URL in a new window
Moreau, L., Ciornei, A., Gjesfjeld, E., Filzmoser, P., Gibson, S. A., Day, J., Nigst, P. R., Noiret, P., Macleod, R. A., Niţă, L., & Anghelinu, M. (2019). First geochemical “fingerprinting” of Balkan and Prut flint from Palaeolithic Romania: potentials, limitations and future directions. Archaeometry, 61(3), 521–538. https://doi.org/10.1111/arcm.12433, opens an external URL in a new window
| First geochemical 'fingerprinting' of Balkan and Prut flint from Palaeolithic Romania: potentials, limitations and future directions at reposiTUm , opens an external URL in a new window
Abreu-Junior, C. H., de Lima Brossi, M. J., Monteiro, R. T., Cardoso, P. H. S., da Silva Mandu, T., Nogueira, T. A. R., Ganga, A., Filzmoser, P., Carvalho de Oliveira, F., Pittol Firme, L., He, Z., & Capra, G. F. (2019). Effects of sewage sludge application on unfertile tropical soils evaluated by multiple approaches: a field experiment in a commercial Eucalyptus plantation. Science of the Total Environment, 655, 1457–1467. https://doi.org/10.1016/j.scitotenv.2018.11.334, opens an external URL in a new window
| Effects of sewage sludge application on unfertile tropical soils evaluated by multiple approaches: a field experiment in a commercial Eucalyptus plantation at reposiTUm , opens an external URL in a new window
Brodinová, Š., Filzmoser, P., Ortner, T., Breiteneder, C., & Rohm, M. (2019). Robust and sparse k-means clustering for high-dimensional data. Advances in Data Analysis and Classification, 905–932. https://doi.org/10.1007/s11634-019-00356-9, opens an external URL in a new window
| Robust and sparse k-means clustering for high-dimensional data at reposiTUm , opens an external URL in a new window
Crocetti, L., Dorigo, W., Martens, B., & Filzmoser, P. (2019). Identifying oceanic-atmospheric controls on hydrology using a machine learning approach. In EGU General Assembly 2019. EGU General Assembly 2019, Vienna, Austria. Copernicus Publications.
| Identifying oceanic-atmospheric controls on hydrology using a machine learning approach at reposiTUm , opens an external URL in a new window
Crocetti, L., Dorigo, W., Martens, B., Filzmoser, P., & Fernandez-Prieto, D. (2019). Impacts of Climatic Oscillations on Mediterranean Hydrology. ESA Living Planet Symposium 2019, Milan, Italy.
| Impacts of Climatic Oscillations on Mediterranean Hydrology at reposiTUm , opens an external URL in a new window
Drastichova, M., & Filzmoser, P. (2019). Assessment of sustainable development using cluster analysis and principal component analysis. Problemy Ekorozwoju, 14(2), 7–24.
| Assessment of sustainable development using cluster analysis and principal component analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Advanced methods of classification and regression. ÖAW AI Summer School 2019, Ligist, Austria.
| Advanced methods of classification and regression at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Buzzword Data Science -- an Overview of Common Methods and their Use in R. Annual Meeting of the Austrian Actuarial Association, Wien, Austria.
| Buzzword Data Science -- an Overview of Common Methods and their Use in R at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Compositional Data Analysis. JOCLAD 2019, Viseu, Portugal.
| Compositional Data Analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Correlation analysis for compositional data. Meet The Jury Seminar, Leuven, Belgium.
| Correlation analysis for compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Correlation analysis for compositional environmental data. Deutsche Statistische Woche, Konstanz, Austria.
| Correlation analysis for compositional environmental data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Linear methods for regression and classification. Data Science School, University of Bolzano, Bozen, Italy.
| Linear methods for regression and classification at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Outlier detection in compositional data: from row-wise to cell-wise. ISI 2019, Kuala Lumpur, Malaysia.
| Outlier detection in compositional data: from row-wise to cell-wise at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Outliers and compositional data. IAMG2019, Pennsylvania, United States of America (the).
| Outliers and compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Potentials of compositional data analysis in practical applications. CARME 2019, Stellenbosch, South Africa.
| Potentials of compositional data analysis in practical applications at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Robust and sparse classification in high dimensions. Seminar presentation, University of Stellenbosch, Institute of Statistics, South Africa.
| Robust and sparse classification in high dimensions at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Robust and sparse estimation methods for linear and logistic regression in high dimensions. DMS-2019, Van, Turkey.
| Robust and sparse estimation methods for linear and logistic regression in high dimensions at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Robust and sparse k-means clustering for high.dimensional data. CDAM 2019, Minsk, Belarus.
| Robust and sparse k-means clustering for high.dimensional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). Robust regression and classification methods for high-dimensional data. Predictive Analytics Konferenz, Wien, Austria.
| Robust regression and classification methods for high-dimensional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). The log-ratio approach to handle relative information. JOCLAD 2019, Viseu, Portugal.
| The log-ratio approach to handle relative information at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2019). k-means clustering for high-dimensional data: a robust and sparse method. ÖSG Statistiktage, Wien, Austria.
| k-means clustering for high-dimensional data: a robust and sparse method at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2019). Comments on: Composition data: the sample space and its structure. TEST, 28(3), 639–643. https://doi.org/10.1007/s11749-019-00671-5, opens an external URL in a new window
| Comments on: Composition data: the sample space and its structure at reposiTUm , opens an external URL in a new window
Filzmoser, P., Brodinova, S., Ortner, T., Breiteneder, C., & Rohm, M. (2019). Robust k-means-based clustering for high-dimensional data. International Conference on Robust Statistics (ICORS 2019), Guayaquil, Ecuador.
| Robust k-means-based clustering for high-dimensional data at reposiTUm , opens an external URL in a new window
Filzmoser, P., Mumic, N., & Kostadinova, R. (2019). Fraud detection in the digital music industry. Benford’s Law Conference, Stresa, Italy.
| Fraud detection in the digital music industry at reposiTUm , opens an external URL in a new window
Lietzen, N., Virta, J., Nordhausen, K., & Ilmonen, P. (2019). Minimum Distance Index for Non-Square Complex Valued Mixing Matrices. In P. Filzmoser & Y. Kharin (Eds.), Proceedings of the 12th International Conference on Computer Data Analysis and Modeling (pp. 79–86). Minsk Publishing Center BSU.
| Minimum Distance Index for Non-Square Complex Valued Mixing Matrices at reposiTUm , opens an external URL in a new window
Miksova, D., Rieser, C., & Filzmoser, P. (2019). Detection of mineralization using the curvature of log‐ratios. CoDaWork 2019, Terrassa, Spain.
| Detection of mineralization using the curvature of log‐ratios at reposiTUm , opens an external URL in a new window
Miksova, D., Rieser, C., & Filzmoser, P. (2019). Identification of mineralization in geochemistry based on the spatial curvature of log-ratio. Olomoucian Days of Applied Mathematics (ODAM 2019), Olomouc, Czechia.
| Identification of mineralization in geochemistry based on the spatial curvature of log-ratio at reposiTUm , opens an external URL in a new window
Miksova, D., Rieser, C., & Filzmoser, P. (2019). Identification of mineralization in geochemistry based on the spatial curvature of log-ratios. In Identification of mineralization in geochemistry based on the spatial curvature of log-ratios (pp. 246–248).
| Identification of mineralization in geochemistry based on the spatial curvature of log-ratios at reposiTUm , opens an external URL in a new window
Rieser, C., & Filzmoser, P. (2019). Piecewise smoothing splines. ÖSG Statistiktage, Wien, Austria.
| Piecewise smoothing splines at reposiTUm , opens an external URL in a new window
Rieser, C., Miksova, D., & Filzmoser, P. (2019). Detection of mineralization using the second derivative of log‐ratios. CoDaWork 2019, Terrassa, Spain.
| Detection of mineralization using the second derivative of log‐ratios at reposiTUm , opens an external URL in a new window
Rosadi, D., & Filzmoser, P. (2019). Robust second-order least-squares estimation for regression models with autoregressive errors. Statistical Papers, 60(1), 105–122. https://doi.org/10.1007/s00362-016-0829-9, opens an external URL in a new window
| Robust second-order least-squares estimation for regression models with autoregressive errors at reposiTUm , opens an external URL in a new window
Templ, M., Gussenbauer, J., & Filzmoser, P. (2019). Evaluation of robust outlier detection methods for zero-inflated complex data. Journal of Applied Statistics, 47(7), 1144–1167. https://doi.org/10.1080/02664763.2019.1671961, opens an external URL in a new window
| Evaluation of robust outlier detection methods for zero-inflated complex data at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., Fray, N., Cottin, H., Merouane, S., Stenzel, O., & Kissel, J. (2019). Composition of cometary particles versus distance to sun during sample collection - based on multivariate evaluation of mass spectral data (Rosetta/COSIMA). Conferentia Chemometrica 2019, Karcag, Hungary.
| Composition of cometary particles versus distance to sun during sample collection - based on multivariate evaluation of mass spectral data (Rosetta/COSIMA). at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., Hilchenbach, M., Kissel, J., Stenzel, O., Merouane, S., & Paquette, J. (2019). Cometary particle surfaces - characterized by chemometric evaluation of secondary ion mass spectra. FKA20, Conference on Solid State Analysis, 20. Tagung Festkörperanalytik, Wien, Austria.
| Cometary particle surfaces - characterized by chemometric evaluation of secondary ion mass spectra. at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., Ortner, T., Hilchenbach, M., Kissel, J., Merouane, S., & Cottin, H. (2019). One-class classification for the recognition of relevant measurements - applied to mass spectra from cometary and meteoritic particles. 16th Scandinavian Symposium on Chemometrics (SSC16), Nesbru / Oslo, Norway.
| One-class classification for the recognition of relevant measurements - applied to mass spectra from cometary and meteoritic particles at reposiTUm , opens an external URL in a new window
Walach, J., Filzmoser, P., Kouřil, Š., Friedecký, D., & Adam, T. (2019). Cellwise outlier detection and biomarker identification in metabolomics based on pairwise log ratios. Journal of Chemometrics, 34(1), Article e3182. https://doi.org/10.1002/cem.3182, opens an external URL in a new window
| Cellwise outlier detection and biomarker identification in metabolomics based on pairwise log ratios at reposiTUm , opens an external URL in a new window
Wurl, A., Falkner, A., Haselböck, A., Mazak, A., & Filzmoser, P. (2019). Exploring robustness in a combined feature selection approach. In Proceedings of the 8th International Conference on Data Science, Technology and Applications. Scitepress - Science and Technology Publications, LDA. https://doi.org/10.5220/0007924400840091, opens an external URL in a new window
| Exploring robustness in a combined feature selection approach. at reposiTUm , opens an external URL in a new window

Landauer, M., Wurzenberger, M., Skopik, F., Settanni, G., & Filzmoser, P. (2018). Dynamic log file analysis: An unsupervised cluster evolution approach for anomaly detection. Computers and Security, 79, 94–116. https://doi.org/10.1016/j.cose.2018.08.009, opens an external URL in a new window
| Dynamic log file analysis: An unsupervised cluster evolution approach for anomaly detection at reposiTUm , opens an external URL in a new window
Reimann, C., Englmaier, P., Flem, B., Eggen, O. A., Finne, T. E., Andersson, M., & Filzmoser, P. (2018). The response of 12 different plant materials and one mushroom to Mo and Pb mineralization along a 100-km transect in southern central Norway. Geochemistry: Exploration, Environment, Analysis, 18(3), 204–215. https://doi.org/10.1144/geochem2017-089, opens an external URL in a new window
| The response of 12 different plant materials and one mushroom to Mo and Pb mineralization along a 100-km transect in southern central Norway at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., Hoffmann, I., Walach, J., Cottin, H., Fray, N., BRIOIS, C., Modica, P., Bardyn, A., Silén, J., Siljeström, S., Stenzel, O., Kissel, J., & Hilchenbach, M. (2018). Significance of variables for discrimination: Applied to the search of organic ions in mass spectra measured on cometary particles. Journal of Chemometrics, 32(4), e3001. https://doi.org/10.1002/cem.3001, opens an external URL in a new window
| Significance of variables for discrimination: Applied to the search of organic ions in mass spectra measured on cometary particles at reposiTUm , opens an external URL in a new window
Brandl, M., Martinez, M. M., Hauzenberger, C., Filzmoser, P., Nymoen, P., & Mehler, N. (2018). A multi-technique analytical approach to sourcing Scandinavian flint: Provenance of ballast flint from the shipwreck “Leirvigen 1”, Norway. PLoS ONE, 13(8), e0200647. https://doi.org/10.1371/journal.pone.0200647, opens an external URL in a new window
| A multi-technique analytical approach to sourcing Scandinavian flint: Provenance of ballast flint from the shipwreck "Leirvigen 1", Norway at reposiTUm , opens an external URL in a new window
Brodinova, S., Zaharieva, M., Filzmoser, P., Ortner, T., & Breiteneder, C. (2018). Clustering of imbalanced high-dimensional media data. Advances in Data Analysis and Classification, 261–284. https://doi.org/10.1007/s11634-017-0292-z, opens an external URL in a new window
| Clustering of imbalanced high-dimensional media data at reposiTUm , opens an external URL in a new window
Capra, G. F., Tidu, S., Lovreglio, R., Certini, G., Salis, M., Bacciu, V., Ganga, A., & Filzmoser, P. (2018). The impact of large fire on calcareous Mediterranean pedosystems (Sardinia, Italy) - An integrated multiple approach. Science of the Total Environment, 624, 1152–1162. https://doi.org/10.1016/j.scitotenv.2017.12.099, opens an external URL in a new window
| The impact of large fire on calcareous Mediterranean pedosystems (Sardinia, Italy) - An integrated multiple approach at reposiTUm , opens an external URL in a new window
Di Palma, M. A., Filzmoser, P., Gallo, M., & Hron, K. (2018). A robust Parafact model for compositional data. Journal of Applied Statistics, 45(8), 1347–1369. https://doi.org/10.1080/02664763.2017.1381669, opens an external URL in a new window
| A robust Parafact model for compositional data at reposiTUm , opens an external URL in a new window
Duarte Silva, A. P., Filzmoser, P., & Brito, P. (2018). Outlier detection in interval data. Advances in Data Analysis and Classification, 12(3), 785–822. https://doi.org/10.1007/s11634-017-0305-y, opens an external URL in a new window
| Outlier detection in interval data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2018). Choice of influencing factors: Lasso. BASF: Data Science Compact Course, Grossraeschen, EU.
| Choice of influencing factors: Lasso at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2018). Estimators for robust maximum association. Modern Stochastics: Theory and Applications, Taras Shevchenko National University of Kyiv, Kiew, Ukraine, Non-EU.
| Estimators for robust maximum association at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2018). Robust and sparse estimation methods for linear and logistic regression in high dimensions. Seminar at the Department of Finance, Accounting and Statistics, Wirtschaftsuniversitaet Wien, WU Wien, Austria.
| Robust and sparse estimation methods for linear and logistic regression in high dimensions at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2018). Robust elastic net (logistic) regression for high dimensional data. Visual Data Science and its role in Computational Medicine, TU Delft, EU.
| Robust elastic net (logistic) regression for high dimensional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2018). Robust estimators of maximum association. ISOR Colloquium at University of Vienna, University of Vienna, Austria.
| Robust estimators of maximum association at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2018). Robust linear and logistic regression in high dimension. Seminar at the Center for Medical Statistics, Informatics, and Intelligent Systems, MedUni Wien, Austria.
| Robust linear and logistic regression in high dimension at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2018). Robust maximum association estimators. Forecasting from Complexity, University of Minnesota, Minneapolis, USA, Non-EU.
| Robust maximum association estimators at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2018). Robust maximum association estimators. International Conference on Robust Statistics (ICORS 2018), KU Leuven, Belgien, EU.
| Robust maximum association estimators at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2018). The log-ratio methodology for compositional data analysis: concepts and applications. Statistische Woche 2018, Linz, Austria.
| The log-ratio methodology for compositional data analysis: concepts and applications at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2018). The log-ratio methodology: Major concepts, robustness, and practical use. International Conference on Computational Statistics (COMPSTAT 2018), Iasi, Romania, EU.
| The log-ratio methodology: Major concepts, robustness, and practical use at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2018). What statistical tool is best? Drawing Insights from Complex Data, TU Wien, Austria.
| What statistical tool is best? at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Kurnaz, F. S. (2018). A robust Liu regression estimator. Communications in Statistics - Simulation and Computation, 47(2), 432–443. https://doi.org/10.1080/03610918.2016.1271889, opens an external URL in a new window
| A robust Liu regression estimator at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., & Templ, M. (2018). Applied Compositional Data Analysis. With Worked Examples in R. Springer Series in Statistics.
| Applied Compositional Data Analysis. With Worked Examples in R at reposiTUm , opens an external URL in a new window
Flem, B., Reimann, C., Fabian, K., Birke, M., Filzmoser, P., & Banks, D. (2018). Graphical statistics to explore the natural and anthropogenic processes influencing the inorganic quality of drinking water, ground water and surface water. Applied Geochemistry, 88, 133–148. https://doi.org/10.1016/j.apgeochem.2017.09.006, opens an external URL in a new window
| Graphical statistics to explore the natural and anthropogenic processes influencing the inorganic quality of drinking water, ground water and surface water at reposiTUm , opens an external URL in a new window
Kurnaz, F. S., Hoffmann, I., & Filzmoser, P. (2018). Robust and sparse estimation methods for high dimensional linear and logistic regression. Chemometrics and Intelligent Laboratory Systems, 172, 211–222. https://doi.org/10.1016/j.chemolab.2017.11.017, opens an external URL in a new window
| Robust and sparse estimation methods for high dimensional linear and logistic regression at reposiTUm , opens an external URL in a new window
Landauer, M., Wurzenberger, M., Skopik, F., Settanni, G., & Filzmoser, P. (2018). Time series analysis: Unsupervised anomaly detection beyond outlier detection. In C. Su & H. Kikuch (Eds.), Information Security Practice and Experience (pp. 16–36). Springer.
| Time series analysis: Unsupervised anomaly detection beyond outlier detection at reposiTUm , opens an external URL in a new window
Mert, M. C., Filzmoser, P., Endel, G., & Wilbacher, I. (2018). Compositional data analysis in epidemiology. Statistical Methods in Medical Research, 27(6), 1878–1891. https://doi.org/10.1177/0962280216671536, opens an external URL in a new window
| Compositional data analysis in epidemiology at reposiTUm , opens an external URL in a new window
Miksova, D., & Filzmoser, P. (2018). Estimation values above an upper detection limit in compositional data. Data Science, Statistics & Visualization (DSSV) 2018, Wien, Austria.
| Estimation values above an upper detection limit in compositional data at reposiTUm , opens an external URL in a new window
Miksova, D., & Filzmoser, P. (2018). Replacement of values above an upper detection limit in compositions. IAMG 2018, Olomouc, EU.
| Replacement of values above an upper detection limit in compositions at reposiTUm , opens an external URL in a new window
Monti, G. S., Filzmoser, P., & Deutsch, R. C. (2018). A robust approach to risk assessment based on species sensitivity distributions. Risk Analysis, 38(10), 2073–2086. https://doi.org/10.1111/risa.13009, opens an external URL in a new window
| A robust approach to risk assessment based on species sensitivity distributions at reposiTUm , opens an external URL in a new window
Ortner, T., Filzmoser, P., Rohm, M., Breiteneder, C., & Brodinova, S. (2018). Guided projections for analyzing the structure of high-dimensional data. Journal of Computational and Graphical Statistics, 27(4), 750–762. https://doi.org/10.1080/10618600.2018.1459304, opens an external URL in a new window
| Guided projections for analyzing the structure of high-dimensional data at reposiTUm , opens an external URL in a new window
Pérez-Fernández, S., Martínez-Camblor, P., Filzmoser, P., & Corral, N. (2018). nsROC: An R package for Non-Standard ROC Curve Analysis. The R Journal, 10(2), 55. https://doi.org/10.32614/rj-2018-043, opens an external URL in a new window
| nsROC: An R package for Non-Standard ROC Curve Analysis at reposiTUm , opens an external URL in a new window
Reimann, C., Fabian, K., Birke, M., Filzmoser, P., Demetriades, A., Négrel, P., Oorts, K., Matschullat, J., & de Caritat, P. (2018). GEMAS: Establishing geochemical back- ground and threshold for 53 chemical elements in European agricultural soil. Applied Geochemistry, 88, 302–318. https://doi.org/10.1016/j.apgeochem.2017.01.021, opens an external URL in a new window
| GEMAS: Establishing geochemical back- ground and threshold for 53 chemical elements in European agricultural soil at reposiTUm , opens an external URL in a new window
Reimann, C., Fabian, K., Flem, B., Anderson, M., Filzmoser, P., & Englmaier, P. (2018). Geosphere-biosphere circulation of chemical elements in soil and plant systems from a 100 km transect from southern central Norway. Science of the Total Environment, 639, 129–145. https://doi.org/10.1016/j.scitotenv.2018.05.070, opens an external URL in a new window
| Geosphere-biosphere circulation of chemical elements in soil and plant systems from a 100 km transect from southern central Norway at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., Hoffmann, I., Hilchenbach, M., Kissel, J., Merouane, S., Paquette, J., & Stenzel, O. (2018). Mass spectrometry near comet 67P (Rosetta/COSIMA). 29th Mass Spec Forum, Wien, Austria.
| Mass spectrometry near comet 67P (Rosetta/COSIMA) at reposiTUm , opens an external URL in a new window
Walach, J., Filzmoser, P., & Hron, K. (2018). The use of log-ratio methodology in cell-wise diagnostic. Data Science, Statistics & Visualization (DSSV) 2018, Wien, Austria.
| The use of log-ratio methodology in cell-wise diagnostic at reposiTUm , opens an external URL in a new window
Walach, J., Filzmoser, P., Hron, K., & Kouril, S. (2018). Cell-wise outlier diagnostics based on pairwise log-ratios. Chemometrics in Analytical Chemistry Conference (CAC), Halifax, Non-EU.
| Cell-wise outlier diagnostics based on pairwise log-ratios at reposiTUm , opens an external URL in a new window
Walach, J., Hron, K., & Filzmoser, P. (2018). Data normalization and scaling: Consequences for the analysis in omics sciences. In J. Jaumot, C. Bedia, & R. Tauler (Eds.), Comprehensive Analytical Chemistry. Data Analysis for Omics Sciences: Methods and Applications (pp. 165–196). Elsevier.
| Data normalization and scaling: Consequences for the analysis in omics sciences at reposiTUm , opens an external URL in a new window
Zimek, A., & Filzmoser, P. (2018). There and back again: Outlier detection between statistical reasoning and data mining algorithms. WIREs Data Mining and Knowledge Discovery, 8(6). https://doi.org/10.1002/widm.1280, opens an external URL in a new window
| There and back again: Outlier detection between statistical reasoning and data mining algorithms at reposiTUm , opens an external URL in a new window

Hron, K., Filzmoser, P., de Caritat, P., Fišerová, E., & Gardlo, A. (2017). Weighted Pivot Coordinates for Compositional Data and Their Application to Geochemical Mapping. Mathematical Geosciences, 49(6), 797–814. https://doi.org/10.1007/s11004-017-9684-z, opens an external URL in a new window
| Weighted Pivot Coordinates for Compositional Data and Their Application to Geochemical Mapping at reposiTUm , opens an external URL in a new window
Stenzel, O., Hilchenbach, M., Merouane, S., Paquette, J., Varmuza, K., Engrand, C., Brandstätter, F., Koeberl, C., Ferrière, L., Filzmoser, P., & Siljeström, S. (2017). Similarities in element content between comet 67P/Churyumov–Gerasimenko coma dust and selected meteorite samples. Monthly Notices of the Royal Astronomical Society, 469(Suppl_2), S492–S505. https://doi.org/10.1093/mnras/stx1908, opens an external URL in a new window
| Similarities in element content between comet 67P/Churyumov–Gerasimenko coma dust and selected meteorite samples at reposiTUm , opens an external URL in a new window
Alfons, A., Croux, C., & Filzmoser, P. (2017). Robust Maximum Association Estimators. Journal of the American Statistical Association, 112(517), 436–445. https://doi.org/10.1080/01621459.2016.1148609, opens an external URL in a new window
| Robust Maximum Association Estimators at reposiTUm , opens an external URL in a new window
Brodinova, S., Filzmoser, P., Ortner, T., Breiteneder, C., & Zaharieva, M. (2017). Finding groups in large and high-dimensional data using a k-means-based algorithm. MOVISS - Metabolomic Bio & Data 2017, Vorau, Austria.
| Finding groups in large and high-dimensional data using a k-means-based algorithm at reposiTUm , opens an external URL in a new window
Brodinova, S., Filzmoser, P., Ortner, T., Zaharieva, M., & Breiteneder, C. (2017). Grouping and outlier detection using robust sparse clustering. Olomouc Days of Applied Mathematics (ODAM 2017), Olomouc, EU.
| Grouping and outlier detection using robust sparse clustering at reposiTUm , opens an external URL in a new window
Brodinova, S., Filzmoser, P., Ortner, T., Zaharieva, M., & Breiteneder, C. (2017). Robust and sparse clustering for high-dimensional data. In CLADAG 2017 Book of Short Papers. Conference of the CLAssification and Data Analysis Group (CLADAG) of the Italian Statistical Society (SIS), Milan, Italy, EU.
| Robust and sparse clustering for high-dimensional data at reposiTUm , opens an external URL in a new window
Bögl, M., Filzmoser, P., Gschwandtner, T., Lammarsch, T., Leite, R. A., Miksch, S., & Rind, A. (2017). Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction. Eurographics / IEEE VGTC Conference on Visualization (EuroVis 2017), Barcelona, Spain, EU.
| Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction at reposiTUm , opens an external URL in a new window
Bögl, M., Filzmoser, P., Gschwandtner, T., Lammarsch, T., Leite, R. A., Miksch, S., & Rind, A. (2017). Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction. Computer Graphics Forum, 36(3), 227–238.
| Cycle Plot Revisited: Multivariate Outlier Detection Using a Distance-Based Abstraction at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2017). Compositional data analysis of geochemical data. Kick-off Project Meeting, Espoo, Finalnd, EU.
| Compositional data analysis of geochemical data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2017). PLS for regression and binary classification: robustness and sparsity. 7th International Chemometrics Research Meeting (ICRM 2017), Berg en Dal, The Netherlands, EU.
| PLS for regression and binary classification: robustness and sparsity at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2017). Robust and sparse estimation methods for high dimensional linear and logistic regression. Workshop devoted to the 60th birthday of Peter Rousseeuw, Leuven. Belgium, EU.
| Robust and sparse estimation methods for high dimensional linear and logistic regression at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2017). Symmetric coordinates for determining pairwise association between compositional parts. CoDaWork 2017, Abbadia San Salvatore, EU.
| Symmetric coordinates for determining pairwise association between compositional parts at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2017). Correlation between variables in compositional data. In EGU General Assembly 2017 (p. 1). Copernicus Publications.
| Correlation between variables in compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Kharin, Y. (2017). Special issue of the CDAM 2016 conference. Austrian Journal of Statistics, 46(3–4), 1–2.
| Special issue of the CDAM 2016 conference at reposiTUm , opens an external URL in a new window
Glock, B., Endel, F., Endel, G., Sandholzer, K., Popper, N., Rinner, C., Duftschmid, G., Filzmoser, P., Mert, M. C., Holl, J., & Wagner-Pinter, M. (2017). How sick is Austria? - A decision support framework for different evaluations of the burden of disease within the Austrian population based on different data sources. International Journal of Population Data Science, 1(1). https://doi.org/10.23889/ijpds.v1i1.111, opens an external URL in a new window
| How sick is Austria? - A decision support framework for different evaluations of the burden of disease within the Austrian population based on different data sources at reposiTUm , opens an external URL in a new window
Grad-Gyenge, L., & Filzmoser, P. (2017). The paradigm of relatedness. In W. Abramowicz, R. Alt, & B. Franczyk (Eds.), Business Information Systems Workshops BIS 2016 International Workshops, Leipzig, Germany, July 6-8, 2016, Revised Papers (pp. 57–68). Springer. https://doi.org/10.1007/978-3-319-52464-1_6, opens an external URL in a new window
| The paradigm of relatedness at reposiTUm , opens an external URL in a new window
Hoffmann, I., Filzmoser, P., & Serneels, S. (2017). Inference for sparse and robust partial least squares regression. Olomouc Days of Applied Mathematics (ODAM 2017), Olomouc, EU.
| Inference for sparse and robust partial least squares regression at reposiTUm , opens an external URL in a new window
Hron, K., Brito, P., & Filzmoser, P. (2017). Exploratory data analysis for interval compositional data. Advances in Data Analysis and Classification, 11(2), 223–241. https://doi.org/10.1007/s11634-016-0245-y, opens an external URL in a new window
| Exploratory data analysis for interval compositional data at reposiTUm , opens an external URL in a new window
Kurnaz, F. S., Hoffmann, I., & Filzmoser, P. (2017). Robust and sparse estimation methods for high dimensional linear and logistic regression. ECDA 2017 - IVth European Conference on Data Analysis 2017, Wroclaw, EU.
| Robust and sparse estimation methods for high dimensional linear and logistic regression at reposiTUm , opens an external URL in a new window
Kurnaz, F. S., Hoffmann, I., & Filzmoser, P. (2017). Robust and sparse methods for high-dimensional linear and logistic regression. MOVISS - Metabolomic Bio & Data 2017, Vorau, Austria.
| Robust and sparse methods for high-dimensional linear and logistic regression at reposiTUm , opens an external URL in a new window
Kynčlová, P., Hron, K., & Filzmoser, P. (2017). Correlation Between Compositional Parts Based on Symmetric Balances. Mathematical Geosciences, 49(6), 777–796. https://doi.org/10.1007/s11004-016-9669-3, opens an external URL in a new window
| Correlation Between Compositional Parts Based on Symmetric Balances at reposiTUm , opens an external URL in a new window
Ortner, T., Filzmoser, P., Brodinova, S., Zaharieva, M., & Breiteneder, C. (2017). Local projection for outlier detection. Olomouc Days of Applied Mathematics (ODAM 2017), Olomouc, EU.
| Local projection for outlier detection at reposiTUm , opens an external URL in a new window
Reimann, C., Filzmoser, P., Hron, K., Kynčlová, P., & Garrett, R. G. (2017). A new method for correlation analysis of compositional (environmental) data - a worked example. Science of the Total Environment, 607–608, 965–971. https://doi.org/10.1016/j.scitotenv.2017.06.063, opens an external URL in a new window
| A new method for correlation analysis of compositional (environmental) data - a worked example at reposiTUm , opens an external URL in a new window
Reimann, C., Négrel, P., Ladenberger, A., Birke, M., Filzmoser, P., O’Connor, P., & Demetriades, A. (2017). Comment on “Maps of heavy metals in the soils of the European Union and proposed priority areas for detailed assessment” by Tóth, G., Hermann, T., Szatmári, G., Pásztor, L. Science of the Total Environment, 578, 236–241. https://doi.org/10.1016/j.scitotenv.2016.07.208, opens an external URL in a new window
| Comment on "Maps of heavy metals in the soils of the European Union and proposed priority areas for detailed assessment" by Tóth, G., Hermann, T., Szatmári, G., Pásztor, L. at reposiTUm , opens an external URL in a new window
Templ, B., Templ, M., Filzmoser, P., Lehoczky, A., Baksiene, E., Fleck, S., Gregow, H., Hodzic, S., Kalvane, G., Kubin, E., Palm, V., Romanovskaja, D., Vucetic, V., Zust, A., & Czúcz, B. (2017). Phenological patterns of flowering across biogeographical regions of Europe. International Journal of Biometeorology, 61(7), 1347–1358. https://doi.org/10.1007/s00484-017-1312-6, opens an external URL in a new window
| Phenological patterns of flowering across biogeographical regions of Europe at reposiTUm , opens an external URL in a new window
Templ, M., Hron, K., & Filzmoser, P. (2017). Exploring outliers in compositional data with structural zeros. CoDaWork 2017, Abbadia San Salvatore, EU.
| Exploring outliers in compositional data with structural zeros at reposiTUm , opens an external URL in a new window
Templ, M., Hron, K., & Filzmoser, P. (2017). Exploratory Tools for Outlier Detection in Compositional Data with Structural Zeros. Journal of Applied Statistics, 44(4), 734–752. https://doi.org/10.1080/02664763.2016.1182135, opens an external URL in a new window
| Exploratory Tools for Outlier Detection in Compositional Data with Structural Zeros at reposiTUm , opens an external URL in a new window
Tobin, J., Walach, J., Beer, D. de, Williams, P., Filzmoser, P., & Walczak, B. (2017). Untargeted analysis of fermentation process of rooibos tea samples. SCC15 2017 - 15th Scandinavian Symposium on Chemometrics, Naantali, Finland, EU.
| Untargeted analysis of fermentation process of rooibos tea samples at reposiTUm , opens an external URL in a new window
Tobin, J., Walach, J., de Beer, D., Williams, P. J., Filzmoser, P., & Walczak, B. (2017). Untargeted analysis of chromatographic data for green and fermented rooibos: problem with size effect removal. Journal of Chromatography A, 1525, 109–115. https://doi.org/10.1016/j.chroma.2017.10.024, opens an external URL in a new window
| Untargeted analysis of chromatographic data for green and fermented rooibos: problem with size effect removal at reposiTUm , opens an external URL in a new window
Varmuza, K., Baklouti, D., Bardyn, A., Cottin, H., Engrand, C., Filzmoser, P., Fray, N., Hilchenbach, M., Hoffmann, I., Kissel, J., Modica, P., Silén, J., Siljeström, S., & Stenzel, O. (2017). Comet dust composition explored by chemometric methods using mass spectral data from COSIMA/ROSETTA. 15th Scandinavian Symposium on Chemometrics (SSC15), Naantali, EU.
| Comet dust composition explored by chemometric methods using mass spectral data from COSIMA/ROSETTA at reposiTUm , opens an external URL in a new window
Varmuza, K., Brandstätter, F., Cottin, H., Engrand, C., Ferrière, L., Filzmoser, P., Fray, N., Hilchenbach, M., Hoffmann, I., Kissel, J., Koeberl, C., Modica, P., Paquette, J., & Stenzel, O. (2017). Comet and meteorite particle surface characterization by multi-variate data analyses using TOF‐SIMS data from COSIMA/Rosetta. ANAKON 2017, Gesellschaft Deutscher Chemiker, Tubingen, EU.
| Comet and meteorite particle surface characterization by multi-variate data analyses using TOF‐SIMS data from COSIMA/Rosetta at reposiTUm , opens an external URL in a new window
Varmuza, K., Brandstätter, F., Cottin, H., Engrand, C., Ferrière, L., Filzmoser, P., Fray, N., Hilchenbach, M., Hoffmann, I., Kissel, J., Koeberl, C., Modica, P., Paquette, J., & Stenzel, O. (2017). Elemental surface composition of comet 67P grains (Rosetta) and of carbonaceous chondrite meteorites - characterized by multivariate mass spectral data (COSIMA). In EGU General Assembly 2017 (p. 1). Copernicus Publications.
| Elemental surface composition of comet 67P grains (Rosetta) and of carbonaceous chondrite meteorites - characterized by multivariate mass spectral data (COSIMA). at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., Hoffmann, I., Walach, J., Cottin, H., Fray, N., Briois, C., Silén, J., Stenzel, O., Kissel, J., & Hilchenbach, M. (2017). Significance of variables for discrimination - applied to the search of organic ions in mass spectra measured on cometary particles. Conferentia Chemometrica 2017, Gyöngyös-Farkasmály, EU.
| Significance of variables for discrimination - applied to the search of organic ions in mass spectra measured on cometary particles at reposiTUm , opens an external URL in a new window
Walach, J., Filzmoser, P., Hron, K., Walczak, B., & Najdekr, L. (2017). A new method for variable selection in a two and multi-group case. ERCIM 2017 - International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2017), London, EU.
| A new method for variable selection in a two and multi-group case at reposiTUm , opens an external URL in a new window
Walach, J., Filzmoser, P., Hron, K., Walczak, B., & Najdekr, L. (2017). A robust pairwise log-ratio approach for variable selection and cell-wise outlier diagnostics with focus on metabolomic data. CoDaWork 2017, Abbadia San Salvatore, EU.
| A robust pairwise log-ratio approach for variable selection and cell-wise outlier diagnostics with focus on metabolomic data at reposiTUm , opens an external URL in a new window
Walach, J., Filzmoser, P., Hron, K., Walczak, B., & Najdekr, L. (2017). Cell-wise outlier diagnostics and its use for biomarker identification. MOVISS - Metabolomic Bio & Data 2017, Vorau, Austria.
| Cell-wise outlier diagnostics and its use for biomarker identification at reposiTUm , opens an external URL in a new window
Walach, J., Filzmoser, P., Hron, K., Walczak, B., & Najdekr, L. (2017). Variable selection method based on a pairwise log-ratio approach and cell-wise outlier diagnostics. Olomouc Days of Applied Mathematics (ODAM 2017), Olomouc, EU.
| Variable selection method based on a pairwise log-ratio approach and cell-wise outlier diagnostics at reposiTUm , opens an external URL in a new window
Walach, J., Filzmoser, P., Hron, K., Walczak, B., & Najdekr, L. (2017). Robust biomarker identification in a two-class problem based on pairwise log-ratios. Chemometrics and Intelligent Laboratory Systems, 171, 277–285. https://doi.org/10.1016/j.chemolab.2017.09.003, opens an external URL in a new window
| Robust biomarker identification in a two-class problem based on pairwise log-ratios at reposiTUm , opens an external URL in a new window
de la Rosa de Sáa, S., Lubiano, M. A., Sinova, B., & Filzmoser, P. (2017). Robust scale estimators for fuzzy data. Advances in Data Analysis and Classification, 11(4), 731–758. https://doi.org/10.1007/s11634-015-0210-1, opens an external URL in a new window
| Robust scale estimators for fuzzy data at reposiTUm , opens an external URL in a new window

Mert, M. C., Filzmoser, P., & Hron, K. (2016). Error propagation in isometric log-ratio coordinates for compositional data: theoretical and practical considerations. Mathematical Geosciences. https://doi.org/10.1007/s11004-016-9646-x, opens an external URL in a new window
| Error propagation in isometric log-ratio coordinates for compositional data: theoretical and practical considerations at reposiTUm , opens an external URL in a new window
Agostinelli, C., Basu, A., Filzmoser, P., & Mukherjee, D. (Eds.). (2016). Recent Advances in Robust Statistics: Theory and Applications. Springer International Publishing. https://doi.org/10.1007/978-81-322-3643-6, opens an external URL in a new window
| Recent Advances in Robust Statistics: Theory and Applications at reposiTUm , opens an external URL in a new window
Alfons, A., Croux, C., & Filzmoser, P. (2016). Robust maximum association between data sets: The R package ccaPP. Austrian Journal of Statistics, 45(1), 71–79. https://doi.org/10.17713/ajs.v45i1.90, opens an external URL in a new window
| Robust maximum association between data sets: The R package ccaPP at reposiTUm , opens an external URL in a new window
Brito, P., Duarte Silva, P., & Filzmoser, P. (2016). Robust multivariate analysis of interval data. SINAPE - Simpósio Nacional de Probabilidade e Estatística - 2016, Porto Allegre, Non-EU.
| Robust multivariate analysis of interval data at reposiTUm , opens an external URL in a new window
Brodinova, S., Ortner, T., Filzmoser, P., Zaharieva, M., & Breiteneder, C. (2016). Evaluation of robust PCA for supervised audio outlier detection. In Proceeding of 22nd International Conference on Computational Statistics (COMPSTAT) (p. 12).
| Evaluation of robust PCA for supervised audio outlier detection at reposiTUm , opens an external URL in a new window
Brodinova, S., Zaharieva, M., Filzmoser, P., Ortner, T., & Breiteneder, C. (2016). Group Detection in the Context of Imbalanced Data. International Conference COMPUTER DATA ANALYSIS & MODELING, Minsk, Belarus, Non-EU.
| Group Detection in the Context of Imbalanced Data at reposiTUm , opens an external URL in a new window
Capra, G. F., Ganga, A., Filzmoser, P., Gaviano, C., & Vacca, S. (2016). Combining local and scientific knowledge on soil resources through an integrated ethnopedological approach. CATENA, 142, 89–101. https://doi.org/10.1016/j.catena.2016.03.003, opens an external URL in a new window
| Combining local and scientific knowledge on soil resources through an integrated ethnopedological approach at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2016). Robust statistics: Theory and practice. Summer School System Simulation Computational Complex Systems, Bad Fischau, Austria.
| Robust statistics: Theory and practice at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2016). Robustness in practice. International Conference of Robust Statistics (ICORS 2016), Genf, Non-EU.
| Robustness in practice at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hoffmann, I., Serneels, S., Croux, C., & Varmuza, K. (2016). Sparse and robust PLS for regression and binary classification. International Conference on Computational Statistics (Compstat 2016), Oviedo, EU.
| Sparse and robust PLS for regression and binary classification at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., & Tolosana-Delgado, R. (2016). Statistical analysis of geochemical compositions: Problems, perspectives and solutions. Applied Geochemistry, 75, 169–170. https://doi.org/10.1016/j.apgeochem.2016.11.016, opens an external URL in a new window
| Statistical analysis of geochemical compositions: Problems, perspectives and solutions at reposiTUm , opens an external URL in a new window
Glock, B., Endel, F., Endel, G., Popper, N., Sandholzer, K., Rinner, C., Duftschmid, G., Holl, J., Wagner-Pinter, M., Mert, M. C., & Filzmoser, P. (2016). How sick is Austria? A decision support framework for different evaluations of the burden of disease within the Austrian population based in different data sources. International Population Data Linkage Conference 2016, Swansea, EU.
| How sick is Austria? A decision support framework for different evaluations of the burden of disease within the Austrian population based in different data sources at reposiTUm , opens an external URL in a new window
Grad-Gyenge, L., & Filzmoser, P. (2016). Recommendation Techniques on a Knowledge Graph for Email Remarketing. In eKNOW 2016, The Eighth International Conference on Information, Process, and Knowledge Management (pp. 51–56). IARIA.
| Recommendation Techniques on a Knowledge Graph for Email Remarketing at reposiTUm , opens an external URL in a new window
Hoffmann, I., Brandstätter, F., Engrand, C., Ferrière, L., Filzmoser, P., Hilchenbach, M., Koeberl, C., & Varmuza, K. (2016). Meteorite classification by TOF-SIMS-chemometrics. 27th Mass Spec Forum Vienna, Wien, Austria.
| Meteorite classification by TOF-SIMS-chemometrics at reposiTUm , opens an external URL in a new window
Hoffmann, I., Filzmoser, P., & Croux, C. (2016). Robust and Sparse Multiclass Classification by the Optimal Scoring Approach. International Conference COMPUTER DATA ANALYSIS & MODELING, Minsk, Belarus, Non-EU.
| Robust and Sparse Multiclass Classification by the Optimal Scoring Approach at reposiTUm , opens an external URL in a new window
Hoffmann, I., Filzmoser, P., & Croux, C. (2016). Robust and sparse classification by the optimal scoring approach. International Conference of the ERCIM WG on Computational and Methodological Statistics, Seville, Spain, EU.
| Robust and sparse classification by the optimal scoring approach at reposiTUm , opens an external URL in a new window
Hoffmann, I., Filzmoser, P., & Croux, C. (2016). Robust and sparse multiclass classification by the optimal scoring approach. International Conference on Robust Statistics, Parma, EU.
| Robust and sparse multiclass classification by the optimal scoring approach at reposiTUm , opens an external URL in a new window
Hoffmann, I., Filzmoser, P., Serneels, S., & Varmuza, K. (2016). Sparse and robust PLS for binary classification. Journal of Chemometrics, 30(4), 153–162. https://doi.org/10.1002/cem.2775, opens an external URL in a new window
| Sparse and robust PLS for binary classification at reposiTUm , opens an external URL in a new window
Hron, K., Filzmoser, P., & Gardlo, A. (2016). Univariate analysis of compositional data using weighted balances. International Conference on Computational Statistics (Compstat 2016), Oviedo, EU.
| Univariate analysis of compositional data using weighted balances at reposiTUm , opens an external URL in a new window
Hron, K., Templ, M., & Filzmoser, P. (2016). Exploring outliers in compositional data with structural zeros. International Conference of the ERCIM WG on Computational and Methodological Statistics, Seville, Spain, EU.
| Exploring outliers in compositional data with structural zeros at reposiTUm , opens an external URL in a new window
Hrůzová, K., Todorov, V., Hron, K., & Filzmoser, P. (2016). Classical and robust orthogonal regression between parts of compositional data. Statistics, 50(6), 1261–1275. https://doi.org/10.1080/02331888.2016.1162164, opens an external URL in a new window
| Classical and robust orthogonal regression between parts of compositional data at reposiTUm , opens an external URL in a new window
Kynčlová, P., Filzmoser, P., & Hron, K. (2016). Compositional biplots including external non-compositional variables. Statistics, 50(5), 1132–1148. https://doi.org/10.1080/02331888.2015.1135155, opens an external URL in a new window
| Compositional biplots including external non-compositional variables at reposiTUm , opens an external URL in a new window
McKinley, J. M., Hron, K., Grunsky, E. C., Reimann, C., de Caritat, P., Filzmoser, P., van den Boogaart, K. G., & Tolosana-Delgado, R. (2016). The single component geochemical map: Fact or fiction? Journal of Geochemical Exploration, 162, 16–28. https://doi.org/10.1016/j.gexplo.2015.12.005, opens an external URL in a new window
| The single component geochemical map: Fact or fiction? at reposiTUm , opens an external URL in a new window
Moreau, L., Brandl, M., Filzmoser, P., Hauzenberger, C., Goemaere, E., Jadin, I., Collet, H., Hanzeur, A., & Schmitz, R. (2016). Geochemical Sourcing of Flint Artifacts from Western Belgium and the German Rhineland: Testing Hypotheses on Gravettian Period Mobility and Raw Material Economy. Geoarchaeology, 31(3), 229–243.
| Geochemical Sourcing of Flint Artifacts from Western Belgium and the German Rhineland: Testing Hypotheses on Gravettian Period Mobility and Raw Material Economy at reposiTUm , opens an external URL in a new window
Ortner, T., Filzmoser, P., Brodinova, S., Zaharieva, M., & Breiteneder, C. (2016). Forward Projection for High-Dimensional Data. International Conference COMPUTER DATA ANALYSIS & MODELING, Minsk, Belarus, Non-EU.
| Forward Projection for High-Dimensional Data at reposiTUm , opens an external URL in a new window
Ortner, T., Filzmoser, P., Zaharieva, M., Breiteneder, C., & Brodinova, S. (2016). Guided projections for analysising the structure of high dimensional data. International Conference of the ERCIM WG on Computational and Methodological Statistics, Seville, Spain, EU.
| Guided projections for analysising the structure of high dimensional data at reposiTUm , opens an external URL in a new window
Reimann, C., Négrel, P., Ladenberger, A., Birke, M., Filzmoser, P., O’Connor, P., & Demetriades, A. (2016). Comment on “Heavy metals in agricultural soil of the European Union with implications for food safety” by G. Toth, T. Hermann, M.R. Da Silva, and L. Montanarella. Environment International, 97, 258–263. https://doi.org/10.1016/j.envint.2016.07.019, opens an external URL in a new window
| Comment on "Heavy metals in agricultural soil of the European Union with implications for food safety" by G. Toth, T. Hermann, M.R. Da Silva, and L. Montanarella at reposiTUm , opens an external URL in a new window
Templ, M., Hron, K., Filzmoser, P., & Gardlo, A. (2016). Imputation of rounded zeros for high-dimensional compositional data. Chemometrics and Intelligent Laboratory Systems, 155, 183–190. https://doi.org/10.1016/j.chemolab.2016.04.011, opens an external URL in a new window
| Imputation of rounded zeros for high-dimensional compositional data at reposiTUm , opens an external URL in a new window
Todorov, V., Hruzova, K., Hron, K., & Filzmoser, P. (2016). An R package for robust orthogonal regression for compositional data. 61^a Reunião Anual da Região Brasileira da Sociedade Internacional de Biometria (RBras 2016), Salvador, Non-EU.
| An R package for robust orthogonal regression for compositional data at reposiTUm , opens an external URL in a new window
Todorov, V., Hruzova, K., Hron, K., & Filzmoser, P. (2016). Robust orthogonal regression for compositional data in R. International Conference of Robust Statistics (ICORS 2016), Genf, Non-EU.
| Robust orthogonal regression for compositional data in R at reposiTUm , opens an external URL in a new window
Walach, J., Filzmoser, P., Hron, K., & Walczak, B. (2016). A Pairwise Log-Ratio Method For The Identification Of Biomarkers. Xvi Chemometrics In Analytical Chemistry, Barcelona, EU.
| A Pairwise Log-Ratio Method For The Identification Of Biomarkers at reposiTUm , opens an external URL in a new window
Walach, J., Filzmoser, P., Hron, K., & Walczak, B. (2016). A Pairwise Log-Ratio Method for the Identification Biomarkers. International Conference COMPUTER DATA ANALYSIS & MODELING, Minsk, Belarus, Non-EU.
| A Pairwise Log-Ratio Method for the Identification Biomarkers at reposiTUm , opens an external URL in a new window

Brodinova, S., Ortner, T., Filzmoser, P., Zaharieva, M., & Breiteneder, C. (2015). Evaluation of Robust PCA for Supervised Audio Outlier Detection (CS-2015-2).
| Evaluation of Robust PCA for Supervised Audio Outlier Detection at reposiTUm , opens an external URL in a new window
Brodinova, S., Ortner, T., Filzmoser, P., Zaharieva, M., & Breiteneder, C. (2015). Simulation of Robust PCA for Supervised Audio Outlier Detection. In Eighth International Workshop on Simulation: Book of Abstracts. International Workshop on Simulation, Vienna, Austria.
| Simulation of Robust PCA for Supervised Audio Outlier Detection at reposiTUm , opens an external URL in a new window
Bögl, M., Aigner, W., Filzmoser, P., Gschwandtner, T., Lammarsch, T., Miksch, S., & Rind, A. (2015). Integrating Predictions in Time Series Model Selection. In J. Yang, E. Bertini, N. Elmqvist, T. Dwyer, X. Yuan, & H. Carr (Eds.), EuroVA 2015 EuroVis Workshop on Visual Analytics (pp. 73–78). The Eurographics Association. https://doi.org/10.2312/eurova.20151107, opens an external URL in a new window
| Integrating Predictions in Time Series Model Selection at reposiTUm , opens an external URL in a new window
Bögl, M., Aigner, W., Filzmoser, P., Gschwandtner, T., Lammarsch, T., Miksch, S., & Rind, A. (2015). Visually and Statistically Guided Imputation of Missing Values in Univariate Seasonal Time Series. In J. Yang, E. Bertini, N. Elmqvist, T. Dwyer, X. Yuan, & H. Carr (Eds.), Poster Proceedings of the IEEE Visualization Conference 2015 (p. 2).
| Visually and Statistically Guided Imputation of Missing Values in Univariate Seasonal Time Series at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2015). Local multivariate outlier identification. Universität Olomouc, Olomouc, EU.
| Local multivariate outlier identification at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2015). Robust statistical methods for high-dimensional data. Isi Wsc World Statistics Congress 2015, Rio de Janeiro, Brazil, Non-EU.
| Robust statistical methods for high-dimensional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2015). Robust statistics and R. In International Conference on Robust Statistics - Book of Abstracts. ICORS 2015 International Conference on Robust Statistics, Indian Statistical Institute, Kolkata, India, Non-EU.
| Robust statistics and R at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2015). Guest Editorial: Special Issue: Compositional Data Modelling. Statistical Modelling, 15(2), vii–viii. https://doi.org/10.1177/1471082x14535520, opens an external URL in a new window
| Guest Editorial: Special Issue: Compositional Data Modelling at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2015). Robust Coordinates for Compositional Data Using Weighted Balances. In K. Nordhausen & S. Taskinen (Eds.), Modern Nonparametric, Robust and Multivariate Methods (pp. 167–184). Springer International Publishing Switzerland. https://doi.org/10.1007/978-3-319-22404-6_10, opens an external URL in a new window
| Robust Coordinates for Compositional Data Using Weighted Balances at reposiTUm , opens an external URL in a new window
Filzmoser, P., Croux, C., Hoffmann, I., & Serneels, S. (2015). High-dimensional regression and classification with sparse partial robust M estimation (IPS067). Isi Wsc World Statistics Congress 2015, Rio de Janeiro, Brazil, Non-EU.
| High-dimensional regression and classification with sparse partial robust M estimation (IPS067) at reposiTUm , opens an external URL in a new window
Filzmoser, P., Gussenbauer, J., & Templ, M. (2015). Detecting outliers in household consumption survey data (Deliverable 4. Contract with world bank (1157976)).
| Detecting outliers in household consumption survey data at reposiTUm , opens an external URL in a new window
Filzmoser, P., Templ, M., & Gussenbauer, J. (2015). Short Overview on Outlier Detection Methods (Deliverable 1 Contract with world bank (1157976)).
| Short Overview on Outlier Detection Methods at reposiTUm , opens an external URL in a new window
Flem, B., Reimann, C., Birke, M., Banks, D., Filzmoser, P., & Frengstad, B. (2015). Inorganic chemical quality of European tap-water: 2. Geographical distribution. Applied Geochemistry, 59, 211–224. https://doi.org/10.1016/j.apgeochem.2015.01.016, opens an external URL in a new window
| Inorganic chemical quality of European tap-water: 2. Geographical distribution at reposiTUm , opens an external URL in a new window
Gardlo, A., Hron, K., Templ, M., & Filzmoser, P. (2015). Imputation of rounded zeros for data from metabolomics. CoDaWork 2015, L’Escala, EU.
| Imputation of rounded zeros for data from metabolomics at reposiTUm , opens an external URL in a new window
Grad-Gyenge, L., Filzmoser, P., & Werthner, H. (2015). Recommendations on a Knowledge Graph. In MLRec 2015 : 1st International Workshop on Machine Learning Methods for Recommender Systems (pp. 13–20).
| Recommendations on a Knowledge Graph at reposiTUm , opens an external URL in a new window
Gussenbauer, J., Filzmoser, P., Templ, M., & Dupriez, O. (2015). Robust Statistical Methods for Outlier Detection with Application to Household Expenditure Data. Statistiktage 2015, Wien, Austria.
| Robust Statistical Methods for Outlier Detection with Application to Household Expenditure Data at reposiTUm , opens an external URL in a new window
Hoffmann, I., Filzmoser, P., & Serneels, S. (2015). Robust and sparse PLS for binary classification. In International Conference on Robust Statistics - Book of Abstracts (pp. 22–23).
| Robust and sparse PLS for binary classification at reposiTUm , opens an external URL in a new window
Hoffmann, I., Serneels, S., Filzmoser, P., & Croux, C. (2015). Sparse partial robust M-regression (CS-2015-1).
| Sparse partial robust M-regression at reposiTUm , opens an external URL in a new window
Hoffmann, I., Serneels, S., Filzmoser, P., & Croux, C. (2015). Sparse partial robust M regression. Chemometrics and Intelligent Laboratory Systems, 149, PART A, 15 DECEMBER, 50–59.
| Sparse partial robust M regression at reposiTUm , opens an external URL in a new window
Hron, K., & Filzmoser, P. (2015). Exploring compositional data with the robust compositional biplot. In M. Carpita, E. Brentari, & E. M. Qannari (Eds.), Advances in Latent Variables. Part of the series Studies in Theoretical and Applied Statistics (pp. 219–226). Springer International Publishing Switzerland.
| Exploring compositional data with the robust compositional biplot at reposiTUm , opens an external URL in a new window
Hron, K., Menafoglio, A., Templ, M., Hruzova, K., & Filzmoser, P. (2015). Simplicial principal component analysis for density functions in Bayes spaces. Computational Statistics & Data Analysis, 94, 330–350. https://doi.org/10.1016/j.csda.2015.07.007, opens an external URL in a new window
| Simplicial principal component analysis for density functions in Bayes spaces at reposiTUm , opens an external URL in a new window
Kalivodova, A., Hron, K., Filzmoser, P., Najdekr, L., Janeckova, H., & Adam, T. (2015). PLS-DA for compositional data with application to metabolomics. Journal of Chemometrics, 29(1), 21–28.
| PLS-DA for compositional data with application to metabolomics at reposiTUm , opens an external URL in a new window
Kynčlová, P., Filzmoser, P., & Hron, K. (2015). Modeling Compositional Time Series with Vector Autoregressive Models. Journal of Forecasting, 34(4 / July), 303–314.
| Modeling Compositional Time Series with Vector Autoregressive Models at reposiTUm , opens an external URL in a new window
Martin-Fernandez, J. A., Hron, K., Templ, M., Filzmoser, P., & Palarea-Albaladejo, J. (2015). Bayesian-multiplicative treatment of count zeros in compositional data sets. Statistical Modelling, 15(2), 134–158.
| Bayesian-multiplicative treatment of count zeros in compositional data sets at reposiTUm , opens an external URL in a new window
Mert, M. C., Filzmoser, P., & Hron, K. (2015). Sparse principal balances. Statistical Modelling, 15(2), 159–174. https://doi.org/10.1177/1471082x14535525, opens an external URL in a new window
| Sparse principal balances at reposiTUm , opens an external URL in a new window
Nordhausen, K., Oja, H., Filzmoser, P., & Reimann, C. (2015). Blind Source Separation for Spatial Compositional Data. Mathematical Geosciences, 47(7), 753–770. https://doi.org/10.1007/s11004-014-9559-5, opens an external URL in a new window
| Blind Source Separation for Spatial Compositional Data at reposiTUm , opens an external URL in a new window
Ortner, T., Filzmoser, P., & Endel, G. (2015). Identifying Structural Changes in Austrian Social Insurance Data. IFAC-PapersOnLine, 48(1), 115–120. https://doi.org/10.1016/j.ifacol.2015.05.152, opens an external URL in a new window
| Identifying Structural Changes in Austrian Social Insurance Data at reposiTUm , opens an external URL in a new window
Szabo, B., Templ, M., Filzmoser, P., Lehoczky, A., & Pongrácz, R. (2015). Biogeographical regions and their flowering phenological patterns across Europe. Phenology 2015, Kusadasi, Non-EU.
| Biogeographical regions and their flowering phenological patterns across Europe at reposiTUm , opens an external URL in a new window
Templ, M., Gussenbauer, J., Filzmoser, P., & Dupriez, O. (2015). Outlier detection in complex survey data including semi-continuous components and missing values. ERCIM 2015, London, EU.
| Outlier detection in complex survey data including semi-continuous components and missing values at reposiTUm , opens an external URL in a new window
Templ, M., Hron, K., Menafoglio, A., Hruskova, K., & Filzmoser, P. (2015). Simplicial principal component analysis for density functions. CoDaWork 2015, L’Escala, EU.
| Simplicial principal component analysis for density functions at reposiTUm , opens an external URL in a new window
Varmuza, K., & Filzmoser, P. (2015). Chapter 2: Repeated Double Cross Validation (rdCV) - A Strategy for Optimizing Empirical Multivariate Models, and for Comparing Their Prediction Performances. In M. Khanmohammadi (Ed.), Current Applications of Chemometrics (pp. 15–32). Nova Science Publishers.
| Chapter 2: Repeated Double Cross Validation (rdCV) - A Strategy for Optimizing Empirical Multivariate Models, and for Comparing Their Prediction Performances at reposiTUm , opens an external URL in a new window
de la Rosa de Sáa, S., Filzmoser, P., Gil, M. Á., & Lubiano, M. A. (2015). On the Robustness of Absolute Deviations with Fuzzy Data. In Strengthening Links Between Data Analysis and Soft Computing (pp. 133–141). Springer Verlag. https://doi.org/10.1007/978-3-319-10765-3_16, opens an external URL in a new window
| On the Robustness of Absolute Deviations with Fuzzy Data at reposiTUm , opens an external URL in a new window

Brandl, M., Hauzenberger, C., Postl, W., Martinez, M. M., Filzmoser, P., & Trnaka, G. (2014). Radiolarite studies at Krems-Wachtberg (Lower Austria): Northern Alpine versus Carpathian lithic resources. Quaternary International, 351, 146–162.
| Radiolarite studies at Krems-Wachtberg (Lower Austria): Northern Alpine versus Carpathian lithic resources at reposiTUm , opens an external URL in a new window
Brito, P., Filzmoser, P., & Hron, K. (2014). Exploratory data analysis for interval compositional data. 4th Workshop in Symbolic Data Analysis (SDA 2014), Taipei, China, Non-EU.
| Exploratory data analysis for interval compositional data at reposiTUm , opens an external URL in a new window
Brito, P., Filzmoser, P., & Hron, K. (2014). Statistical analysis of interval compositional data. In CFE-ERCIM 2014 - Book of Abstracts. ERCIM 2014 - 7th International Conference of the ERCIM WG on Computational and Methodological Statistics, University of Pisa, Italy, EU.
| Statistical analysis of interval compositional data at reposiTUm , opens an external URL in a new window
Bögl, M., Aigner, W., Filzmoser, P., Gschwandtner, T., Lammarsch, T., Miksch, S., & Rind, A. (2014). Visual Analytics Methods to Guide Diagnostics for Time Series Model Predictions. In Proceedings of the 2014 IEEE VIS Workshop on Visualization for Predictive Analytics (p. 4).
| Visual Analytics Methods to Guide Diagnostics for Time Series Model Predictions at reposiTUm , opens an external URL in a new window
Demetriades, A., Reimann, C., & Filzmoser, P. (2014). Evaluation of GEMAS project quality control results. In C. Reimann, M. Birke, A. Demetriades, P. Filzmoser, & P. O´Connor (Eds.), Chemistry of Europe’s Agricultural Soils. Part A: Methodology and Interpretation of the GEMAS Data Set, Geologisches Jahrbuch, Reihe B, Heft 102 (pp. 47–60). E. Schweizerbart’sche Verlagsbuchhandlung oHG.
| Evaluation of GEMAS project quality control results at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2014). Generalized additive models. Seminar at the Palacky University, Olomouc / Czech Republic, Non-EU.
| Generalized additive models at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2014). Identi cation of multivariate outliers in interval data. Seminar at the Palacky University, Olomouc / Czech Republic, Non-EU.
| Identi cation of multivariate outliers in interval data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2014). Identifikation multivariater Ausreißer bei Intervalldaten. Stochastik - Workshop Innsbruck (in Kooperation mit TU Dresden), Innsbruck, Austria.
| Identifikation multivariater Ausreißer bei Intervalldaten at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2014). Opportunities of compositional data analysis in chemometrics. CAC 2014 - 14th Conference on Chemometrics in Analytical Chemistry, Richmond, Virginia, EU.
| Opportunities of compositional data analysis in chemometrics at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2014). PCA and beyond. Seminar for students of the Palacký University, Velké Losiny, EU.
| PCA and beyond at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2014). Robust statistics: theoretical and practical considerations. Seminar for students of the Palacký University, Dolni Morava, Cz, EU.
| Robust statistics: theoretical and practical considerations at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2014). Spline interpolation. Seminar at the Palacky University, Olomouc / Czech Republic, Non-EU.
| Spline interpolation at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2014). Statistical analysis of interval compositional data. Seminar at the Lisbon University of Technology, Lisbon, Portugal, EU.
| Statistical analysis of interval compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Reimann, C. (2014). Multivariate data analysis. In C. Reimann, M. Birke, A. Demetriades, P. Filzmoser, & P. O´Connor (Eds.), Chemistry of Europe’s Agricultural Soils. Part A: Methodology and Interpretation of the GEMAS Data Set, Geologisches Jahrbuch, Reihe B, Heft 102 (pp. 83–92). E. Schweizerbart’sche Verlagsbuchhandlung oHG.
| Multivariate data analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Walczak, B. (2014). What can go wrong at the data normalization step for identification of biomarkers? Journal of Chromatography A, 1362, 194–205. https://doi.org/10.1016/j.chroma.2014.08.050, opens an external URL in a new window
| What can go wrong at the data normalization step for identification of biomarkers? at reposiTUm , opens an external URL in a new window
Filzmoser, P., Brito, P., & Pedro Duarte Silva, A. (2014). Outlier detection in interval data. In M. Gilli, G. Gonzalez-Rodriguez, & A. Nieto-Reyes (Eds.), Proceedings of COMPSTAT 2014 (p. 11).
| Outlier detection in interval data at reposiTUm , opens an external URL in a new window
Filzmoser, P., Gatu, C., & Zeileis, A. (2014). Special issue on statistical algorithms and software in R. Computational Statistics & Data Analysis, 71, 887–888. https://doi.org/10.1016/j.csda.2013.10.012, opens an external URL in a new window
| Special issue on statistical algorithms and software in R at reposiTUm , opens an external URL in a new window
Filzmoser, P., Reimann, C., & Birke, M. (2014). Statistical aspects when analyzing geochemical compositions. EGU European Geosciences Union General Assembly 2014, Vienna, Austria.
| Statistical aspects when analyzing geochemical compositions at reposiTUm , opens an external URL in a new window
Filzmoser, P., Reimann, C., & Birke, M. (2014). Univariate data analysis and mapping. In C. Reimann, M. Birke, A. Demetriades, P. Filzmoser, & P. O´Connor (Eds.), Chemistry of Europe’s Agricultural Soils. Part A: Methodology and Interpretation of the GEMAS Data Set, Geologisches Jahrbuch, Reihe B, Heft 102 (pp. 67–81). E. Schweizerbart’sche Verlagsbuchhandlung oHG.
| Univariate data analysis and mapping at reposiTUm , opens an external URL in a new window
Filzmoser, P., Ruiz-Gazen, A., & Thomas-Agnan, C. (2014). Identification of local multivariate outliers. Statistical Papers, 55(1), 29–47. https://doi.org/10.1007/s00362-013-0524-z, opens an external URL in a new window
| Identification of local multivariate outliers at reposiTUm , opens an external URL in a new window
Grad-Gyenge, L., Werthner, H., & Filzmoser, P. (2014). Spreading Activation for Rating Estimation in Recommender Systems. The 15th International Conference on Electronic Commerce and Web Technologies (EC-Web 2014), Munich, Germany, EU.
| Spreading Activation for Rating Estimation in Recommender Systems at reposiTUm , opens an external URL in a new window
Hron, K., Filzmoser, P., Templ, M., van den Boogaart, K. G., & Tolosana-Delgado, R. (2014). Robust Regression with Compositional Response: Application to Geosciences. In Mathematics of Planet Earth. Proceedings of the 15th Annual Conference of the International Association for Mathematical Geosciences (pp. 87–90). Springer Verlag Berlin-Heidelberg. https://doi.org/10.1007/978-3-642-32408-6_21, opens an external URL in a new window
| Robust Regression with Compositional Response: Application to Geosciences at reposiTUm , opens an external URL in a new window
Hron, K., Menafoglio, A., Templ, M., Hruzova, K., & Filzmoser, P. (2014). Simplicial principal component analysis for density functions in Bayes spaces (MOX-report 25/2014).
| Simplicial principal component analysis for density functions in Bayes spaces at reposiTUm , opens an external URL in a new window
Hron, K., Menafoglio, A., Templ, M., Hruzova, K., & Filzmoser, P. (2014). Simplicial principal component analysis for density functions in Bayes spaces. In CFE-ERCIM 2014 - Book of Abstracts. ERCIM 2014 - 7th International Conference of the ERCIM WG on Computational and Methodological Statistics, University of Pisa, Italy, EU.
| Simplicial principal component analysis for density functions in Bayes spaces at reposiTUm , opens an external URL in a new window
Huf, W., Kalcher, K., Boubela, R. N., Rath, G., Vecsei, A., Filzmoser, P., & Moser, E. (2014). On the generalizability of resting-state fMRI machine learning classifiers. Frontiers in Human Neuroscience, 8. https://doi.org/10.3389/fnhum.2014.00502, opens an external URL in a new window
| On the generalizability of resting-state fMRI machine learning classifiers at reposiTUm , opens an external URL in a new window
Kalcher, K., Boubela, R. N., Huf, W., Bartova, L., Kronnerwetter, C., Derntl, B., Pezawas, L., Filzmoser, P., Nasel, C., & Moser, E. (2014). The Spectral Diversity of Resting-State Fluctuations in the Human Brain. PLoS ONE, 9(4), e93375. https://doi.org/10.1371/journal.pone.0093375, opens an external URL in a new window
| The Spectral Diversity of Resting-State Fluctuations in the Human Brain at reposiTUm , opens an external URL in a new window
Kalivodova, A., Hron, K., & Filzmoser, P. (2014). PLS-DA for metabolomical (compositional) data using the logratio approach. In CFE-ERCIM 2014 - Book of Abstracts. ERCIM 2014 - 7th International Conference of the ERCIM WG on Computational and Methodological Statistics, University of Pisa, Italy, EU.
| PLS-DA for metabolomical (compositional) data using the logratio approach at reposiTUm , opens an external URL in a new window
Kynčlová, P., Filzmoser, P., & Hron, K. (2014). Application of T-spaces in modeling compositional time series. In CFE-ERCIM 2014 - Book of Abstracts. ERCIM 2014 - 7th International Conference of the ERCIM WG on Computational and Methodological Statistics, University of Pisa, Italy, EU.
| Application of T-spaces in modeling compositional time series at reposiTUm , opens an external URL in a new window
Ladenberger, A., Uhlbäck, J., Andersson, M., Reimann, C., Tarvainen, T., Morris, G., Sadeghi, M., Eklund, M., & Filzmoser, P. (2014). Elemental patterns in agricultural and grazing land soil in Norway, Finland and Sweden: What have we learned from continental scale mapping. In C. Reimann, M. Birke, A. Demetriades, P. Filzmoser, & P. O´Connor (Eds.), Chemistry of Europe’s Agricultural Soils. Part A: Methodology and Interpretation of the GEMAS Data Set, Geologisches Jahrbuch, Reihe B, Heft 103 (pp. 235–251). E. Schweizerbart’sche Verlagsbuchhandlung oHG.
| Elemental patterns in agricultural and grazing land soil in Norway, Finland and Sweden: What have we learned from continental scale mapping. at reposiTUm , opens an external URL in a new window
Mert, M. C., Filzmoser, P., & Hron, K. (2014). Error propagation of compositional data transformations. In CFE-ERCIM 2014 - Book of Abstracts. ERCIM 2014 - 7th International Conference of the ERCIM WG on Computational and Methodological Statistics, University of Pisa, Italy, EU.
| Error propagation of compositional data transformations at reposiTUm , opens an external URL in a new window
Neykov, N. M., Filzmoser, P., & Neytchev, P. N. (2014). Ultrahigh dimensional variable selection through the penalized maximum trimmed likelihood estimator. Statistical Papers, 55(1), 187–207. https://doi.org/10.1007/s00362-013-0516-z, opens an external URL in a new window
| Ultrahigh dimensional variable selection through the penalized maximum trimmed likelihood estimator at reposiTUm , opens an external URL in a new window
Neykov, N., Filzmoser, P., & Neytchev, P. (2014). Robust variable selection in joint modeling of location, scale and shape for high dimensional data through trimming (CS6). In ICORS14 - Conference Guide & Book of Abstracts (p. 39).
| Robust variable selection in joint modeling of location, scale and shape for high dimensional data through trimming (CS6) at reposiTUm , opens an external URL in a new window
Nordhausen, K., Oja, H., Filzmoser, P., & Reimann, C. (2014). Blind source separation for spatial compositional data. Mathematical Geosciences, 47(7), 753–770. https://doi.org/10.1007/s11004-014-9559-5, opens an external URL in a new window
| Blind source separation for spatial compositional data at reposiTUm , opens an external URL in a new window
Nordhausen, K., Oja, H., Filzmoser, P., & Reimann, C. (2014). Blind source separation for spatial compositional data. In CFE-ERCIM 2014 - Book of Abstracts. ERCIM 2014 - 7th International Conference of the ERCIM WG on Computational and Methodological Statistics, University of Pisa, Italy, EU.
| Blind source separation for spatial compositional data at reposiTUm , opens an external URL in a new window
Reimann, C., Birke, M., Demetriades, A., & Filzmoser, P. (Eds.). (2014). Chemistry of Europe’s Agricultural Soils Part A and B (2-volume set), 880 pp | 1 DVD | Hardbound ISBN 978-3-510-96848-0. E. Schweizerbart’sche Verlagsbuchhandlung oHG.
| Chemistry of Europe's Agricultural Soils Part A and B (2-volume set), 880 pp | 1 DVD | Hardbound ISBN 978-3-510-96848-0 at reposiTUm , opens an external URL in a new window
Reimann, C., Birke, M., Demetriades, A., Filzmoser, P., & O´Connor, P. (Eds.). (2014). Part A: Methodology and Interpretation of the GEMAS Data Set. E. Schweizerbart’sche Verlagsbuchhandlung oHG.
| Part A: Methodology and Interpretation of the GEMAS Data Set at reposiTUm , opens an external URL in a new window
Reimann, C., Birke, M., Demetriades, A., Filzmoser, P., & O´Connor, P. (Eds.). (2014). Part B: General Background Information and Further Analysis of the GEMAS Data Set. E. Schweizerbart’sche Verlagsbuchhandlung oHG.
| Part B: General Background Information and Further Analysis of the GEMAS Data Set at reposiTUm , opens an external URL in a new window
Reimann, C., Filzmoser, P., & Hron, K. (2014). Geochemical mapping and CoDa: Problems and Possibilities. In K. Hron & P. Filzmoser (Eds.), GeoMap Workshop Proceedings (pp. 47–49). Palacký University, Olomouc, Cz.
| Geochemical mapping and CoDa: Problems and Possibilities at reposiTUm , opens an external URL in a new window
Reimann, C., Filzmoser, P., & Hron, K. (Eds.). (2014). GeoMap Workshop Proceedings. Palacký University, Olomouc, Cz.
| GeoMap Workshop Proceedings at reposiTUm , opens an external URL in a new window
Reitner, H., Filzmoser, P., & Pirkl, H. (2014). Subject to Change: A log-ra! o approach to the geochemistry of stream sediment samples. In K. Hron & P. Filzmoser (Eds.), GeoMap Workshop Proceedings (pp. 50–52). Palacký University, Olomouc, Cz.
| Subject to Change: A log-ra! o approach to the geochemistry of stream sediment samples at reposiTUm , opens an external URL in a new window
Serneels, S., Filzmoser, P., Hoffmann, I., & Croux, C. (2014). Sparse partial robust M regression. In ICORS14 - Conference Guide & Book of Abstracts (p. 24).
| Sparse partial robust M regression at reposiTUm , opens an external URL in a new window
Special Issue - 10th International Conference COMPUTER DATA ANALYSIS & MODELLING 2013, Minsk, Belarus ( Vol.43, 3-4). (2014). In P. Filzmoser & M. Templ (Eds.), Austrian Journal of Statistics. Österreichische Statistische Gesellschaft.
| Special Issue - 10th International Conference COMPUTER DATA ANALYSIS & MODELLING 2013, Minsk, Belarus ( Vol.43, 3-4) at reposiTUm , opens an external URL in a new window
Stenzel, O., Varmuza, K., Engrand, C., Ferrière, L., Brandstätter, F., Koeberl, C., Filzmoser, P., & Hilchenbach, M. (2014). Characterisation of meteoritic samples with the Rosetta Cosima TOF-SIMS laboratory reference model - a covariance approach. In Asteroids, Comets, Meteors, Book of Abstracts, Helsinki, Finland, 2014 Editors: K. Muinonen, A. Penttilä, M. Granvik, A. Virkki, G. Fedorets, O. Wilkman, T. Kohout. ACM 2014 - Asteroids, Comets, Meteors, Helsinki / Finland, EU.
| Characterisation of meteoritic samples with the Rosetta Cosima TOF-SIMS laboratory reference model - a covariance approach at reposiTUm , opens an external URL in a new window
Szabo, B., Lehoczky, A., Filzmoser, P., Templ, M., Szentkirályi, F., Pongrácz, R., Ortner, T., Mert, M. C., & Czúcz, B. (2014). From South to North: flowering phenological responses at different geographical latitudes in 12 European countries. European Geosciences Union General Assembly 2014, Wien, Austria.
| From South to North: flowering phenological responses at different geographical latitudes in 12 European countries at reposiTUm , opens an external URL in a new window
Templ, M., & Filzmoser, P. (2014). Simulation and quality of a synthetic close-to-reality employer-employee population. Journal of Applied Statistics, 41(5), 1053–1072. https://doi.org/10.1080/02664763.2013.859237, opens an external URL in a new window
| Simulation and quality of a synthetic close-to-reality employer-employee population at reposiTUm , opens an external URL in a new window
Templ, M., Alfons, A., & Filzmoser, P. (2014). Robust Estimation of Income and Social Indicators with Tail Modelling. Seminar in Applied Mathematics, Palacky University Olomouc, EU.
| Robust Estimation of Income and Social Indicators with Tail Modelling at reposiTUm , opens an external URL in a new window
Templ, M., Hron, K., & Filzmoser, P. (2014). The Problem of Missing Values and Rounded Zeros in Compositional Data. Joint Statistical Meeting, Vancouver, Canada, Non-EU.
| The Problem of Missing Values and Rounded Zeros in Compositional Data at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2014). Software tools for robust analysis of high-dimensional data. Austrian Journal of Statistics, 43(4), 255–266. https://doi.org/10.17713/ajs.v43i4.44, opens an external URL in a new window
| Software tools for robust analysis of high-dimensional data at reposiTUm , opens an external URL in a new window
Tolosana-Delgado, R., van den Boogaart, K. G., Filzmoser, P., Hron, K., & Templ, M. (2014). Compositional regression: an overview. IAMG2014 - 16th Annual Conference of the International Association for Mathematical Geosciences, New Delhi, Non-EU.
| Compositional regression: an overview at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., Hilchenbach, M., Krüger, H., & Silén, J. (2014). KNN classification - evaluated by repeated double cross validation: Recognition of minerals relevant for comet dust. Chemometrics and Intelligent Laboratory Systems, 138, 64–71. https://doi.org/10.1016/j.chemolab.2014.07.011, opens an external URL in a new window
| KNN classification - evaluated by repeated double cross validation: Recognition of minerals relevant for comet dust at reposiTUm , opens an external URL in a new window

Bögl, M., Aigner, W., Filzmoser, P., Lammarsch, T., Miksch, S., & Rind, A. (2013). Visual Analytics for Model Selection in Time Series Analysis. IEEE Transactions on Visualization and Computer Graphics, 19(12), 2237–2246. https://doi.org/10.1109/tvcg.2013.222, opens an external URL in a new window
| Visual Analytics for Model Selection in Time Series Analysis at reposiTUm , opens an external URL in a new window
Aivazian, S., Filzmoser, P., & Kharin, Y. (2013). Greetings from the Programm Committee Co-Chairs. In S. Aivazian, P. Filzmoser, & Y. Kharin (Eds.), Computer Data Analysis and Modeling - Theoretical and Applied Stochastics / Proceedings of the Tenth International Conference Minsk, September 10-14, 2013 (pp. 5–6). Publishing center BSU, Minsk.
| Greetings from the Programm Committee Co-Chairs at reposiTUm , opens an external URL in a new window
Aivazian, S., Filzmoser, P., & Kharin, Y. (Eds.). (2013). Computer Data Analysis and Modeling Theoretical and Applied Stochastics / Proceedings of the Tenth International Conference, Minsk. Publishing center BSU, Minsk.
| Computer Data Analysis and Modeling Theoretical and Applied Stochastics / Proceedings of the Tenth International Conference, Minsk at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2013). Robust estimation of economic indicators from survey samples based on Pareto tail modelling. Journal of the Royal Statistical Society: Series C, VOL. 62(2), 271–286.
| Robust estimation of economic indicators from survey samples based on Pareto tail modelling at reposiTUm , opens an external URL in a new window
Ballabio, D., Vasighi, M., & Filzmoser, P. (2013). Effects of supervised Self Organising Maps parameters on classification performance. Analytica Chimica Acta, 765, 45–53. https://doi.org/10.1016/j.aca.2012.12.027, opens an external URL in a new window
| Effects of supervised Self Organising Maps parameters on classification performance at reposiTUm , opens an external URL in a new window
Boubela, R. N., Kalcher, K., Huf, W., Kronnerwetter, C., Filzmoser, P., & Moser, E. (2013). Beyond noise: Using temporal ICA to extract meaningful information from high-frequency fMRI signal fluctuations during rest. Frontiers in Human Neuroscience, 7. https://doi.org/10.3389/fnhum.2013.00168, opens an external URL in a new window
| Beyond noise: Using temporal ICA to extract meaningful information from high-frequency fMRI signal fluctuations during rest at reposiTUm , opens an external URL in a new window
Brandl, M., Filzmoser, P., & Hauzenberger, C. (2013). Northern Alpine versus Carpatian radiolarites - a case study from the Upper Palaeolithic Krems-Wachtberg site (Lower Austria). In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria (p. 16).
| Northern Alpine versus Carpatian radiolarites - a case study from the Upper Palaeolithic Krems-Wachtberg site (Lower Austria) at reposiTUm , opens an external URL in a new window
Bögl, M., Aigner, W., Filzmoser, P., Lammarsch, T., Miksch, S., & Rind, A. (2013). Visual Analytics for Model Selection in Time Series Analysis. IEEE Conference on Visual Analytics Science and Technology (IEEE VAST), Atlanta, GA, USA, Non-EU.
| Visual Analytics for Model Selection in Time Series Analysis at reposiTUm , opens an external URL in a new window
Croux, C., Filzmoser, P., & Fritz, H. (2013). Robust Sparse Principal Component Analysis. Technometrics, 55(2), 202–214. https://doi.org/10.1080/00401706.2012.727746, opens an external URL in a new window
| Robust Sparse Principal Component Analysis at reposiTUm , opens an external URL in a new window
Donevska, S., Fiserová, E., Filzmoser, P., & Hron, K. (2013). Covariance-based variable selection for compositional data. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria (p. 23).
| Covariance-based variable selection for compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Advanced methods for regression and classi cation, and how to use them in R. ECO Winter School 2013, Kalmar, Sweden, EU.
| Advanced methods for regression and classi cation, and how to use them in R at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Computational statistics: The ATC/ICD project and applications. Workshop on Innovative Methods for Evidence Based Decision Making in Healthcare, Vienna, Austria.
| Computational statistics: The ATC/ICD project and applications at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Concepts of compositional data analysis. Seminar at the Institute for Water Quality, Resource and Waste Management, Vienna, Austria.
| Concepts of compositional data analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Linear and non-linear methods for regression and classification. Workshop at the University of Debrecen, Hungary, EU.
| Linear and non-linear methods for regression and classification at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Multivariate Regression und Klassi kation mit Anwendungen aus der Chemometrie. Herbstseminar der Wiener Biometrischen Sektion, Vienna, Austria.
| Multivariate Regression und Klassi kation mit Anwendungen aus der Chemometrie at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Outlier detection in compositional data with structural zeros. ODAM 2013 - Olomoucian Days of Applied Mathematics, Olomouc, EU.
| Outlier detection in compositional data with structural zeros at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Robust Linear Regression for Compositional Data. ICORS 2013 International Conference on Robust Statistics, Saint Petersburg, Russia, Non-EU.
| Robust Linear Regression for Compositional Data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Robust dimension reduction for high-dimensional data. Universität Olomouc, Olomouc, EU.
| Robust dimension reduction for high-dimensional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Robust variable selection in linear regression with compositional explanatory variables. Seminar at the University of Geneve, Genf, Schweiz, Non-EU.
| Robust variable selection in linear regression with compositional explanatory variables at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Sparse multivariate statistical methods for high-dimensional data. Seminar at the University of Bergen, Bergen, Norway, EU.
| Sparse multivariate statistical methods for high-dimensional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Sparse regression and classi cation methods for high-dimensional data. Seminar at the Vienna PhD-School of Informatics, Technical University Vienna, Austria.
| Sparse regression and classi cation methods for high-dimensional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Stepwise variable selection in robust regression with compositional explanatory variables. ODAM 2013 - Olomoucian Days of Applied Mathematics, Olomouc, EU.
| Stepwise variable selection in robust regression with compositional explanatory variables at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Support vector machine. Seminar at the Palacky University, Olomouc / Czech Republic, Non-EU.
| Support vector machine at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Variable selection in regression models. Universität Olomouc, Olomouc, EU.
| Variable selection in regression models at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Analysis of chemical data from a compositional point of view. In VIII Colloquium Chemometricum Mediterraneum (p. 8).
| Analysis of chemical data from a compositional point of view at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Compositional data and R. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria.
| Compositional data and R at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). Opening Lecture: A Projection-Pursuit Method for Sparse Robust PCA. In Proceedings of the 10th International Conderence Computer Data Analysis & Modelling 2013. CDAM 2013 10th International Conference Computer Data Analysis & Modeling 2013 Theoretical & Applied Stochastics, Minsk, Weißrussland, Belarus, Non-EU.
| Opening Lecture: A Projection-Pursuit Method for Sparse Robust PCA at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2013). R Tools for Robust Statistical Analysis of High-Dimensional Data. In Proceedings of the 10th International Conderence Computer Data Analysis & Modelling 2013. CDAM 2013 10th International Conference Computer Data Analysis & Modeling 2013 Theoretical & Applied Stochastics, Minsk, Weißrussland, Belarus, Non-EU.
| R Tools for Robust Statistical Analysis of High-Dimensional Data at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2013). Robustness for Compositional Data. In C. Becker, R. Fried, & S. Kuhnt (Eds.), Robustness and Complex Data Structures (pp. 117–131). Springer Verlag. https://doi.org/10.1007/978-3-642-35494-6_8, opens an external URL in a new window
| Robustness for Compositional Data at reposiTUm , opens an external URL in a new window
Filzmoser, P., Croux, C., & Fritz, H. (2013). Sparse and robust principal component analysis. DAGStat 2013, Freiburg, Deutschland, EU.
| Sparse and robust principal component analysis at reposiTUm , opens an external URL in a new window
Gschwandtner, M., & Filzmoser, P. (2013). Outlier Detection in High Dimension Using Regularization. In Synergies of Soft Computing and Statistics for Intelligent Data Analysis (pp. 237–244). Springer Verlag Berlin-Heidelberg. https://doi.org/10.1007/978-3-642-33042-1_26, opens an external URL in a new window
| Outlier Detection in High Dimension Using Regularization at reposiTUm , opens an external URL in a new window
Hron, K., & Filzmoser, P. (2013). Exploring compositional data with the robust compositional biplot. SIS 2013 - Advances in Latent Variables - Methods, Models and Applications, Brescia, Italy, EU.
| Exploring compositional data with the robust compositional biplot at reposiTUm , opens an external URL in a new window
Hron, K., & Filzmoser, P. (2013). Robust Diagnostics of Fuzzy Clustering Results Using the Compositional Approach. In Synergies of Soft Computing and Statistics for Intelligent Data Analysis (pp. 245–253). Springer Verlag Berlin-Heidelberg. https://doi.org/10.1007/978-3-642-33042-1_27, opens an external URL in a new window
| Robust Diagnostics of Fuzzy Clustering Results Using the Compositional Approach at reposiTUm , opens an external URL in a new window
Hron, K., Filzmoser, P., & Fiserová, E. (2013). Correlation analysis for compositional data using classical and robust methods. ODAM 2013 - Olomoucian Days of Applied Mathematics, Olomouc, EU.
| Correlation analysis for compositional data using classical and robust methods at reposiTUm , opens an external URL in a new window
Hron, K., Filzmoser, P., & Templ, M. (Eds.). (2013). Proceedings of the 5th International Workshop on compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria. TU WIEN.
| Proceedings of the 5th International Workshop on compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria at reposiTUm , opens an external URL in a new window
Hron, K., Filzmoser, P., Donevska, S., & Fišerová, E. (2013). Covariance-based variable selection for compositional data. Mathematical Geosciences, 45(4), 487–498. https://doi.org/10.1007/s11004-013-9450-9, opens an external URL in a new window
| Covariance-based variable selection for compositional data at reposiTUm , opens an external URL in a new window
Hron, K., Templ, M., & Filzmoser, P. (2013). Estimation of a proportion in survey sampling using the logratio approach. Metrika, 76(6), 799–818. https://doi.org/10.1007/s00184-012-0416-6, opens an external URL in a new window
| Estimation of a proportion in survey sampling using the logratio approach at reposiTUm , opens an external URL in a new window
Kalcher, K., Boubela, R., Huf, W., Biswal, B., Baldinger, P., Sailer, U., Filzmoser, P., Kasper, S., Lamm, C., Lanzenberger, R., & Moser, E. (2013). RESCALE: Voxel-specific Task-fMRI Scaling Using Resting State Fluctuation Amplitude. NeuroImage, 70(15 April), 80–88.
| RESCALE: Voxel-specific Task-fMRI Scaling Using Resting State Fluctuation Amplitude at reposiTUm , opens an external URL in a new window
Kalidova, A., Hron, K., Templ, M., & Filzmoser, P. (2013). Replacement of Missing Values and Rounded Zeros in High-Dimensional Compositional Data with Application to Metabolomics. ODAM 2013 - Olomoucian Days of Applied Mathematics, Olomouc, EU.
| Replacement of Missing Values and Rounded Zeros in High-Dimensional Compositional Data with Application to Metabolomics at reposiTUm , opens an external URL in a new window
Kynčlová, P., Filzmoser, P., & Hron, K. (2013). How to Model Compositional Time Series from the Official Statistics Chair: Österreichische Statistiktage 2013, Statistik Austria, Wien, Austria.
| How to Model Compositional Time Series from the Official Statistics Chair: at reposiTUm , opens an external URL in a new window
Kynčlová, P., Filzmoser, P., & Hron, K. (2013). Vector autoregression for compositiona; time series. ODAM 2013 - Olomoucian Days of Applied Mathematics, Olomouc, EU.
| Vector autoregression for compositiona; time series at reposiTUm , opens an external URL in a new window
Kynčlová, P., Filzmoser, P., & Hron, K. (2013). Compositional time series: The VAR model. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria (p. 39).
| Compositional time series: The VAR model at reposiTUm , opens an external URL in a new window
Martinez Avila, J. C., Filzmoser, P., & Neykov, N. (2013). Statistical modeling of hunting success using hunter surveys. Austrian Journal of Statistics, 42(2), 67–80.
| Statistical modeling of hunting success using hunter surveys at reposiTUm , opens an external URL in a new window
Mert, M. C., Filzmoser, P., & Hron, K. (2013). Principal balances with sparse PCA. ODAM 2013 - Olomoucian Days of Applied Mathematics, Olomouc, EU.
| Principal balances with sparse PCA at reposiTUm , opens an external URL in a new window
Mert, M. C., Filzmoser, P., & Hron, K. (2013). Sparse Principal Balances for High-Dimensional Compositional Data. In Proceedings of the 10th International Conderence Computer Data Analysis & Modelling 2013. CDAM 2013 10th International Conference Computer Data Analysis & Modeling 2013 Theoretical & Applied Stochastics, Minsk, Weißrussland, Belarus, Non-EU. Publishing Center of BSU Minsk 2013.
| Sparse Principal Balances for High-Dimensional Compositional Data at reposiTUm , opens an external URL in a new window
Mert, M. C., Filzmoser, P., & Hron, K. (2013). Sparse principal balances. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria (pp. 44–45).
| Sparse principal balances at reposiTUm , opens an external URL in a new window
Monti, G., Hron, K., Filzmoser, P., & Templ, M. (2013). Covariance-Based Outlier Detection for Compositional Data with Structural Zeros: Application to Italian Survey of Household Income and Wealth Data. SIS 2013 - Advances in Latent Variables - Methods, Models and Applications, Brescia, Italy, EU.
| Covariance-Based Outlier Detection for Compositional Data with Structural Zeros: Application to Italian Survey of Household Income and Wealth Data at reposiTUm , opens an external URL in a new window
Monti, G., Hron, K., Filzmoser, P., & Templ, M. (2013). Covariance-Based Outlier Detection for Compositional Data with Structural Zeros: Application to Italian Survey of Household Income and Wealth Data. In D. Vita e Pensiero (Ed.), Dipartimento di Economia, Metodi Quantitativi e Strategie di Impresa. Vita e Pensiero.
| Covariance-Based Outlier Detection for Compositional Data with Structural Zeros: Application to Italian Survey of Household Income and Wealth Data at reposiTUm , opens an external URL in a new window
Reimann, C., Filzmoser, P., & Hron, K. (2013). Challenges for CoDa in geochemical practice. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria (p. 52).
| Challenges for CoDa in geochemical practice at reposiTUm , opens an external URL in a new window
Schroeder, F., Braumann, A., Filzmoser, P., & Hron, K. (2013). Robust variable selection in linear regression with compositional explanatory variables. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria (p. 55).
| Robust variable selection in linear regression with compositional explanatory variables at reposiTUm , opens an external URL in a new window
Templ, M. (2013). Supporting tools. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria.
| Supporting tools at reposiTUm , opens an external URL in a new window
Templ, M., Aklan, S., Filzmoser, P., Preusser, M., & Hainfellner, J. A. (2013). Statistical Indicators for the Analysis of Digitalized Brain Tumor Images. Austrian Journal of Statistics, 42(2), 1–19. https://doi.org/10.17713/ajs.v42i2.156, opens an external URL in a new window
| Statistical Indicators for the Analysis of Digitalized Brain Tumor Images at reposiTUm , opens an external URL in a new window
Templ, M., Hron, K., & Filzmoser, P. (2013). The R packages robCompositions and compositionsGUI. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria.
| The R packages robCompositions and compositionsGUI at reposiTUm , opens an external URL in a new window
Templ, M., Hron, K., Filzmoser, P., & Monti, G. (2013). Methods to Detect Outliers in Compositional Data with Structural Zeros. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria (p. 56).
| Methods to Detect Outliers in Compositional Data with Structural Zeros at reposiTUm , opens an external URL in a new window
Templ, M., van den Boogaart, G., Eichler, J., Filzmoser, P., Hron, K., & Tolosana-Delgado, R. (2013). Software compositionsGUI. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria.
| Software compositionsGUI at reposiTUm , opens an external URL in a new window
Todeschini, R., Ballabio, D., Consonni, V., Sahigara, F., & Filzmoser, P. (2013). Locally-centred Mahalanobis distance: a new distance measure with salient features towards outlier detection. Analytica Chimica Acta, 787, 1–9. https://doi.org/10.1016/j.aca.2013.04.034, opens an external URL in a new window
| Locally-centred Mahalanobis distance: a new distance measure with salient features towards outlier detection at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2013). Multivariate robust partial M-regression. ICORS 2013 International Conference on Robust Statistics, Saint Petersburg, Russia, Non-EU.
| Multivariate robust partial M-regression at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2013). Comparing Classical and Robust Sparse PCA. In Synergies of Soft Computing and Statistics for Intelligent Data Analysis (pp. 283–291). Springer Verlag Berlin-Heidelberg. https://doi.org/10.1007/978-3-642-33042-1_31, opens an external URL in a new window
| Comparing Classical and Robust Sparse PCA at reposiTUm , opens an external URL in a new window
Todorov, V., Facevicova, K., Hron, K., Guo, D., & Templ, M. (2013). Statistical analysis of compositional 2x2 tables with an economic application. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria (p. 58).
| Statistical analysis of compositional 2x2 tables with an economic application at reposiTUm , opens an external URL in a new window
Varmuza, K., & Filzmoser, P. (2013). Variable selection and its strict evaluation. CC 2013 Conferentia Chemometrica 2013, Sopron / Hungary, EU.
| Variable selection and its strict evaluation at reposiTUm , opens an external URL in a new window
Varmuza, K., Dehmer, M., & Filzmoser, P. (2013). Empirical modeling of mass spectral features by molecular descriptors. CC 2013 Conferentia Chemometrica 2013, Sopron / Hungary, EU.
| Empirical modeling of mass spectral features by molecular descriptors at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., & Dehmer, M. (2013). Multivariate linear QSPR/QSAR models: Rigorous evaluation of variable selection for PLS. Computational and Structural Biotechnology Journal, 5(e201302007), e201302007. https://doi.org/10.5936/csbj.201302007, opens an external URL in a new window
| Multivariate linear QSPR/QSAR models: Rigorous evaluation of variable selection for PLS at reposiTUm , opens an external URL in a new window
Zehetgruber, J., Filzmoser, P., Hron, K., & Templ, M. (2013). Robust multivariate regression with compositional data. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria (p. 65).
| Robust multivariate regression with compositional data at reposiTUm , opens an external URL in a new window
de la Rosa de Saa, S., Filzmoser, P., Gil, M. A., & Lubiano, M. A. (2013). Fuzzy rating or fuzzy linguistic? ODAM 2013 - Olomoucian Days of Applied Mathematics, Olomouc, EU.
| Fuzzy rating or fuzzy linguistic? at reposiTUm , opens an external URL in a new window
van den Boogaart, G., Tolosana-Delgado, R., Hron, K., Templ, M., & Filzmoser, P. (2013). Compositional regression with unobserved components or below detection limit values. In K. Hron, P. Filzmoser, & M. Templ (Eds.), Proceedings of the 5th International Workshop on Compositional Data Analysis CoDaWork 2013 June 3-7, 2013, Vorau, Austria (p. 59).
| Compositional regression with unobserved components or below detection limit values at reposiTUm , opens an external URL in a new window

Boubela, R. N., Huf, W., Kalcher, K., Sladky, R., Filzmoser, P., Pezawas, L., Kasper, S., Windischberger, C., & Moser, E. (2012). A highly parallelized framework for computationally intensive MR data analysis. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE, 25(4), 313–320. https://doi.org/10.1007/s10334-011-0290-7, opens an external URL in a new window
| A highly parallelized framework for computationally intensive MR data analysis at reposiTUm , opens an external URL in a new window
Alfons, A., Croux, C., & Filzmoser, P. (2012). A projection-pursuit algorithm for robust maximum correlation estimators. Statistische Woche 2012, TU Wien, Austria.
| A projection-pursuit algorithm for robust maximum correlation estimators at reposiTUm , opens an external URL in a new window
Alfons, A., Croux, C., & Filzmoser, P. (2012). Robust maximum correlation based on projection pursuit. International Conference on Robust Statistics, Parma, EU.
| Robust maximum correlation based on projection pursuit at reposiTUm , opens an external URL in a new window
Boubela, R., Kalcher, K., Huf, W., Moser, E., Windischberger, C., & Filzmoser, P. (2012). A highly parallelized statistical analysis of fMRI data in R. Statistische Woche 2012, TU Wien, Austria.
| A highly parallelized statistical analysis of fMRI data in R at reposiTUm , opens an external URL in a new window
Egozcue, J. J., Daunis-I-Estadella, J., Pawlowsky-Glahn, V., Hron, K., & Filzmoser, P. (2012). Simplicial regression. The normal model. Journal of Applied Probability and Statistics, 6, 87–108.
| Simplicial regression. The normal model at reposiTUm , opens an external URL in a new window
Endel, G., Pfeffer, N., Wilbacher, I., Filzmoser, P., Endel, F., Eisl, A., Dorda, W., Duftschmid, G., Grossmann, W., Schober, E., & Waldhör, T. (2012). Burden of disease of Diabetes Mellitus - consequences for capacity planning. 9th HTAi Annual Meeting. HTA in Integrated Care for a Patient Centered System, Bilbao / Spain, EU.
| Burden of disease of Diabetes Mellitus - consequences for capacity planning at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2012). Compositional data analysis: Consequences for Chemometrics. Afrodatat 2012, Stellenbosch / South Africa, Non-EU.
| Compositional data analysis: Consequences for Chemometrics at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2012). Introduction to concepts of robust statistics. Seminar at the Palacky University, Olomouc / Czech Republic, Non-EU.
| Introduction to concepts of robust statistics at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2012). Regression and Classification Methods for High-dimensional Data. Seminar at the Palacky University, Olomouc / Czech Republic, Non-EU.
| Regression and Classification Methods for High-dimensional Data at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2012). Compositional data analysis: challenges for environment sciences. University Venice, Venice / Italy, Austria.
| Compositional data analysis: challenges for environment sciences at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2012). Correlation Analysis for Compositional Data. Mathematical Geosciences, 41(8), 905–919. https://doi.org/10.1007/s11004-008-9196-y, opens an external URL in a new window
| Correlation Analysis for Compositional Data at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Todorov, V. (2012). Robust tools for the imperfect world. Information Sciences, 245, 4–20. https://doi.org/10.1016/j.ins.2012.10.017, opens an external URL in a new window
| Robust tools for the imperfect world at reposiTUm , opens an external URL in a new window
Filzmoser, P., Croux, C., & Fritz, H. (2012). Robust Sparse Principal Component Analysis. Austrian Statistical Society, Vienna, Austria.
| Robust Sparse Principal Component Analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P., Croux, C., & Fritz, H. (2012). Robust sparse PCA in R. In Proceedings COMPSTAT2012. International Conference on Computational Statistics, Limassol / Cyprus, EU.
| Robust sparse PCA in R at reposiTUm , opens an external URL in a new window
Filzmoser, P., Gschwandtner, M., & Todorov, V. (2012). Review of sparse methods in regression and classification with application to chemometrics. Seminar at the National Insitute of Chemistry, Ljubljana / Slovenia, EU.
| Review of sparse methods in regression and classification with application to chemometrics at reposiTUm , opens an external URL in a new window
Filzmoser, P., Gschwandtner, M., & Todorov, V. (2012). Sparse statistical methods: theory, applications, software. ECO Summer School, Verona / Italy, EU.
| Sparse statistical methods: theory, applications, software at reposiTUm , opens an external URL in a new window
Filzmoser, P., Gschwandtner, M., & Todorov, V. (2012). Review of sparse methods in regression and classification with application to chemometrics. Journal of Chemometrics, 26, 10.
| Review of sparse methods in regression and classification with application to chemometrics at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., & Reimann, C. (2012). Interpretation of multivariate outliers for compositional data. Computers and Geosciences, 39, 77–85. https://doi.org/10.1016/j.cageo.2011.06.014, opens an external URL in a new window
| Interpretation of multivariate outliers for compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., & Templ, M. (2012). Discriminant analysis for compositional data and robust parameter estimation. Computational Statistics, 27(4), 585–604. https://doi.org/10.1007/s00180-011-0279-8, opens an external URL in a new window
| Discriminant analysis for compositional data and robust parameter estimation at reposiTUm , opens an external URL in a new window
Filzmoser, P., Neykov, N., & Neytchev, P. (2012). Robust ultrahigh-dimensional variable selection through trimming. International Conference on Robust Statistics, Parma, EU.
| Robust ultrahigh-dimensional variable selection through trimming at reposiTUm , opens an external URL in a new window
Filzmoser, P., Ruiz-Gazen, A., & Thomas-Agnan, C. (2012). Identification of local multivariate outliers. Workshop on Statistical Methods for Dependent Data, Witten / Germany, EU.
| Identification of local multivariate outliers at reposiTUm , opens an external URL in a new window
Fritz, H., Filzmoser, P., & Croux, C. (2012). A comparison of algorithms for the multivariate L1-median. Computational Statistics, 27(3), 393–410. https://doi.org/10.1007/s00180-011-0262-4, opens an external URL in a new window
| A comparison of algorithms for the multivariate L1-median at reposiTUm , opens an external URL in a new window
Gschwandtner, M., & Filzmoser, P. (2012). Outlier detection by the use of the regularized MCD estimator. Statistische Woche 2012, TU Wien, Austria.
| Outlier detection by the use of the regularized MCD estimator at reposiTUm , opens an external URL in a new window
Hron, K., & Filzmoser, P. (2012). Classical and robust correlation analysis of compositional data. Statistische Woche 2012, TU Wien, Austria.
| Classical and robust correlation analysis of compositional data at reposiTUm , opens an external URL in a new window
Hron, K., & Filzmoser, P. (2012). Robust diagnostics of fuzzy clustering results using the compositional approach. International Conference on Soft Methods in Probability and Statistics SMPS2012, Konstanz / Germany, Austria.
| Robust diagnostics of fuzzy clustering results using the compositional approach at reposiTUm , opens an external URL in a new window
Hron, K., Filzmoser, P., & Thompson, K. (2012). Linear regression with compositional explanatory variables. Journal of Applied Statistics, 39(5), 1115–1128. https://doi.org/10.1080/02664763.2011.644268, opens an external URL in a new window
| Linear regression with compositional explanatory variables at reposiTUm , opens an external URL in a new window
Hron, K., Filzmoser, P., Templ, M., van den Boogaart, G., & Tolosana-Delgado, R. (2012). A unified approach to classical and robust regression for compositional data. 5th International Conference of the ERCIM WG on COMPUTING & STATISTICS, Oviedo / Spain, EU.
| A unified approach to classical and robust regression for compositional data at reposiTUm , opens an external URL in a new window
Hron, K., Jelínková, M., Filzmoser, P., Kreuziger, R., Bednář, P., & Barták, P. (2012). Statistical analysis of wines using a robust compositional biplot. Talanta, 90, 46–50. https://doi.org/10.1016/j.talanta.2011.12.060, opens an external URL in a new window
| Statistical analysis of wines using a robust compositional biplot at reposiTUm , opens an external URL in a new window
Kalcher, K., Huf, W., Boubela, R. N., Filzmoser, P., Pezawas, L., Biswal, B., Kasper, S., Moser, E., & Windischberger, C. (2012). Fully exploratory network independent component analysis of the 1000 functional connectomes database. Frontiers in Human Neuroscience, 6. https://doi.org/10.3389/fnhum.2012.00301, opens an external URL in a new window
| Fully exploratory network independent component analysis of the 1000 functional connectomes database at reposiTUm , opens an external URL in a new window
Katschnig, H., Endel, F., Endel, G., Weibold, B., Scheffel, S., & Filzmoser, P. (2012). Dementia and pathways of health service utilisation in Austria: A record linkage study in a country with a fragmented provider payment system. 22nd Alzheimer Europe Conference, Vienna, Austria.
| Dementia and pathways of health service utilisation in Austria: A record linkage study in a country with a fragmented provider payment system at reposiTUm , opens an external URL in a new window
Kehrer, J., Boubela, R. N., Filzmoser, P., & Piringer, H. (2012). A generic model for the integration of interactive visualization and statistical computing using R. In 2012 IEEE Conference on Visual Analytics Science and Technology (VAST). IEEE Conference on Visual Analytics Science and Technology, VAST 2012, Seattle, WA, USA, Non-EU. https://doi.org/10.1109/vast.2012.6400537, opens an external URL in a new window
| A generic model for the integration of interactive visualization and statistical computing using R at reposiTUm , opens an external URL in a new window
Liebmann, B., Todeschini, R., Cansonni, V., Filzmoser, P., & Varmuza, K. (2012). Variable selection by the LASSO method. Conference on Chemometrics in Analytic Chemistry, Budapest / Hungary, EU.
| Variable selection by the LASSO method at reposiTUm , opens an external URL in a new window
Liebmann, B., Todeschini, R., Consonni, V., Filzmoser, P., & Varmuza, K. (2012). Variable Selection by the LASSO method. In XIII Chemometrics in Analytical Chemistry (p. 161).
| Variable Selection by the LASSO method at reposiTUm , opens an external URL in a new window
Martin-Fernandez, J. A., Hron, K., Templ, M., Filzmoser, P., & Palarea-Albaladejo, J. (2012). Evaluating the performance of a Bayesian-multiplicative treatment of zeros in compositional data sets. In Proceedings of COMPSTAT2012. International Conference on Computational Statistics, Limassol / Cyprus, EU.
| Evaluating the performance of a Bayesian-multiplicative treatment of zeros in compositional data sets at reposiTUm , opens an external URL in a new window
Martín-Fernández, J. A., Hron, K., Templ, M., Filzmoser, P., & Palarea-Albaladejo, J. (2012). Model-based replacement of rounded zeros in compositional data: Classical and robust approaches. Computational Statistics & Data Analysis, 56(9), 2688–2704. https://doi.org/10.1016/j.csda.2012.02.012, opens an external URL in a new window
| Model-based replacement of rounded zeros in compositional data: Classical and robust approaches at reposiTUm , opens an external URL in a new window
Neykov, N. M., Filzmoser, P., & Neytchev, P. N. (2012). Robust joint modeling of mean and dispersion through trimming. Computational Statistics & Data Analysis, 56(1), 34–48. https://doi.org/10.1016/j.csda.2011.07.007, opens an external URL in a new window
| Robust joint modeling of mean and dispersion through trimming at reposiTUm , opens an external URL in a new window
Neykov, N. M., Čížek, P., Filzmoser, P., & Neytchev, P. N. (2012). The least trimmed quantile regression. Computational Statistics & Data Analysis, 56(6), 1757–1770. https://doi.org/10.1016/j.csda.2011.10.023, opens an external URL in a new window
| The least trimmed quantile regression at reposiTUm , opens an external URL in a new window
Neykov, N., Filzmoser, P., & Neytchev, P. (2012). Robust estimation in high demensional GLMs through trimming. Workshop on Statistical Methods for Dependent Data, Witten / Germany, EU.
| Robust estimation in high demensional GLMs through trimming at reposiTUm , opens an external URL in a new window
Pascoal, C., de Oliviera, M. R., Valades, R., Filzmoser, P., Salvador, P., & Pacheco, A. (2012). Robust feature selection and robust PCA for internet traffic anomaly detection. In 2012 Proceedings IEEE INFOCOM. 31th International Conference on Computer Communications IEEE, Orlando / Florida, Non-EU. https://doi.org/10.1109/infcom.2012.6195548, opens an external URL in a new window
| Robust feature selection and robust PCA for internet traffic anomaly detection at reposiTUm , opens an external URL in a new window
Reimann, C., Birke, M., & Filzmoser, P. (2012). Temperature-dependent leaching of chemical elements from mineral water bottle materials. Applied Geochemistry, 27(8), 1492–1498. https://doi.org/10.1016/j.apgeochem.2012.05.003, opens an external URL in a new window
| Temperature-dependent leaching of chemical elements from mineral water bottle materials at reposiTUm , opens an external URL in a new window
Reimann, C., Filzmoser, P., Fabian, K., Hron, K., Birke, M., Demetriades, A., Dinelli, E., & Ladenberger, A. (2012). The concept of compositional data analysis in practice - Total major element concentrations in agricultural and grazing land soils of Europe. Science of the Total Environment, 426, 196–210. https://doi.org/10.1016/j.scitotenv.2012.02.032, opens an external URL in a new window
| The concept of compositional data analysis in practice - Total major element concentrations in agricultural and grazing land soils of Europe at reposiTUm , opens an external URL in a new window
Schroeder, F., Braumann, A., & Filzmoser, P. (2012). Robust variable selection for linear regression models with compositional data. Statistische Woche 2012, TU Wien, Austria.
| Robust variable selection for linear regression models with compositional data at reposiTUm , opens an external URL in a new window
Sucharovà, J., Suchara, I., Hola, M., Marikova, S., Reimann, C., Boyd, R., Filzmoser, P., & Englmaier, P. (2012). Top-/bottom-soil ratios and enrichment factors: What do they really show? Applied Geochemistry, 27(1), 138–145. https://doi.org/10.1016/j.apgeochem.2011.09.025, opens an external URL in a new window
| Top-/bottom-soil ratios and enrichment factors: What do they really show? at reposiTUm , opens an external URL in a new window
Templ, M., Alfons, A., & Filzmoser, P. (2012). Exploring incomplete data using visualization techniques. Advances in Data Analysis and Classification, 6(1), 29–47. https://doi.org/10.1007/s11634-011-0102-y, opens an external URL in a new window
| Exploring incomplete data using visualization techniques at reposiTUm , opens an external URL in a new window
Templ, M., Hulliger, B., & Kowarik, A. (2012). Visualization of regional indicators with the checkerplot. In P. Filzmoser (Ed.), Book of Abstracts (p. 141).
| Visualization of regional indicators with the checkerplot at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2012). Comparing classical and robust sparse PCA. International Conference on Soft Methods in Probability and Statistics SMPS2012, Konstanz / Germany, Austria.
| Comparing classical and robust sparse PCA at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2012). Sparse and robust partial least squares regression. 5th International Conference of the ERCIM WG on COMPUTING & STATISTICS, Oviedo / Spain, EU.
| Sparse and robust partial least squares regression at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2012). Sparse and robust partial least squares regression. Statistische Woche 2012, TU Wien, Austria.
| Sparse and robust partial least squares regression at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2012). rrcovHD: Moving rrcov to high dimensions. International Conference on Robust Statistics, Parma, EU.
| rrcovHD: Moving rrcov to high dimensions at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., Liebmann, B., & Dehmer, M. (2012). Redundancy analysis for characterizing the correlation between groups of variables - Applied to molecular descriptors. Chemometrics and Intelligent Laboratory Systems, 117, 31–41. https://doi.org/10.1016/j.chemolab.2011.05.013, opens an external URL in a new window
| Redundancy analysis for characterizing the correlation between groups of variables - Applied to molecular descriptors at reposiTUm , opens an external URL in a new window
Varmuza, K., Liebmann, B., & Filzmoser, P. (2012). Repeated double cross validation for optimization and evaluation of empirical classifiers. In XIII Chemometrics in Analytical Chemistry (p. 160).
| Repeated double cross validation for optimization and evaluation of empirical classifiers at reposiTUm , opens an external URL in a new window

Turkay, C., Filzmoser, P., & Hauser, H. (2011). Brushing Dimensions - A Dual Visual Analysis Model for High-Dimensional Data. IEEE Transactions on Visualization and Computer Graphics, 17(12), 2591–2599. https://doi.org/10.1109/TVCG.2011.178, opens an external URL in a new window
| Brushing Dimensions - A Dual Visual Analysis Model for High-Dimensional Data at reposiTUm , opens an external URL in a new window
Suchara, I., Sucharova, J., Hola, M., Reimann, C., Boyd, R., Filzmoser, P., & Englmaier, P. (2011). The performance of moss, grass, and 1- and 2-year old spruce needles as bioindicators of contamination: A comparative study at the scale of the Czech Republic. Science of the Total Environment, 409(11), 2281–2297. https://doi.org/10.1016/j.scitotenv.2011.02.003, opens an external URL in a new window
| The performance of moss, grass, and 1- and 2-year old spruce needles as bioindicators of contamination: A comparative study at the scale of the Czech Republic at reposiTUm , opens an external URL in a new window
Sucharova, J., Suchara, I., Hola, M., Reimann, C., Boyd, R., Filzmoser, P., & Englmaier, P. (2011). Linking chemical elements in forest floor humus (Oₕ-horizon) in the Czech Republic to contamination sources. Environmental Pollution, 159(5), 1205–1214. https://doi.org/10.1016/j.envpol.2011.01.041, opens an external URL in a new window
| Linking chemical elements in forest floor humus (Oₕ-horizon) in the Czech Republic to contamination sources at reposiTUm , opens an external URL in a new window
Alfons, A., & Filzmoser, P. (2011). Robust variable selection with application in the social sciences. Dutch/Flemish Classification Society Spring Meeting, Antwerpen, EU.
| Robust variable selection with application in the social sciences at reposiTUm , opens an external URL in a new window
Alfons, A., Baaske, W. E., Filzmoser, P., Mader, W., & Wieser, R. (2011). Robust variable selection with application to quality of life research. Statistical Methods & Applications, 20(1), 65–82. https://doi.org/10.1007/s10260-010-0151-y, opens an external URL in a new window
| Robust variable selection with application to quality of life research at reposiTUm , opens an external URL in a new window
Alfons, A., Burgard, J. P., Filzmoser, P., Hulliger, B., Kolb, J.-P., Kraft, S., Münnich, R., Schoch, T., & Templ, M. (2011). The AMELI simulation study (European Commission,FP7-SSH-2007-217322,WP6-D6.1).
| The AMELI simulation study at reposiTUm , opens an external URL in a new window
Alfons, A., Filzmoser, P., & Templ, M. (2011). Summary of the State-of-the-art in visualisation of the European Laeken Indicators (European Commission,FP7-SSH-2007-217322,WP1-D1.1-6).
| Summary of the State-of-the-art in visualisation of the European Laeken Indicators at reposiTUm , opens an external URL in a new window
Alfons, A., Filzmoser, P., Hulliger, B., Kolb, J.-P., Kraft, S., Münnich, R., & Templ, M. (2011). Synthetic data generation of SILC (European Commission,FP7-SSH-2007-217322,WP6-D6.2-3).
| Synthetic data generation of SILC at reposiTUm , opens an external URL in a new window
Alfons, A., Filzmoser, P., Kraft, S., & Templ, M. (2011). The R package simFrame (European Commission,FP7-SSH-2007-217322,WP6-D6.1-3).
| The R package simFrame at reposiTUm , opens an external URL in a new window
Alfons, A., Filzmoser, P., Kraft, S., Templ, M., Kolb, J.-P., & Münnich, R. (2011). Design-based simulations (European Commission,FP7-SSH-2007-217322,WP6-D6.1-2).
| Design-based simulations at reposiTUm , opens an external URL in a new window
Alfons, A., Filzmoser, P., Meraner, A., & Templ, M. (2011). Robust distribution fitting (European Commission,FP7-SSH-2007-217322,WP4-D4.1-3).
| Robust distribution fitting at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2011). Applications of statistical simulation (Europ. Commission,FP7-SSH-2007-21732,WP10-D10.3-2).
| Applications of statistical simulation at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2011). Robust semiparametric estimation of economic indicators from survey samples (CS-2011-5).
| Robust semiparametric estimation of economic indicators from survey samples at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2011). Simulation of EU-SILC population data using simPopulation (Europ. Commission,FP7-SSH-2007-21732,WP10-D10.3-3).
| Simulation of EU-SILC population data using simPopulation at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2011). Robust estimation of social inclusion indicators based on Pareto tail modeling. In Proceedings of the NTTS 2011 conference (p. 3).
| Robust estimation of social inclusion indicators based on Pareto tail modeling at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2011). Simulation of close-to-reality population data for household surveys with application to EU-SILC. Statistical Methods & Applications, 20(3), 383–407. https://doi.org/10.1007/s10260-011-0163-2, opens an external URL in a new window
| Simulation of close-to-reality population data for household surveys with application to EU-SILC at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., Filzmoser, P., & Holzer, J. (2011). Robust Pareto tail modeling for the estimation of indicators on social exclusion using the R package laeken (CS-2011-2).
| Robust Pareto tail modeling for the estimation of indicators on social exclusion using the R package laeken at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., Filzmoser, P., & Holzer, J. (2011). Robust Pareto tail modeling with package laeken (Europ. Commission,FP7-SSH-2007-21732,WP10-D10.3-6).
| Robust Pareto tail modeling with package laeken at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., Filzmoser, P., & Holzer, J. (2011). Semi-parametric robust estimation (Europ. Commission,FP7-SSH-2007-21732,WP4-D4.2-3).
| Semi-parametric robust estimation at reposiTUm , opens an external URL in a new window
Berger, W., Piringer, H., Filzmoser, P., & Gröller, E. (2011). Uncertainty-Aware Exploration of Continuous Parameter Spaces Using Multivariate Prediction. EuroVis 2011, Bergen, Norway, EU.
| Uncertainty-Aware Exploration of Continuous Parameter Spaces Using Multivariate Prediction at reposiTUm , opens an external URL in a new window
Berger, W., Piringer, H., Filzmoser, P., & Gröller, E. (2011). Uncertainty-Aware Exploration of Continuous Parameter Spaces Using Multivariate Prediction. Computer Graphics Forum, 30(3), 911–920.
| Uncertainty-Aware Exploration of Continuous Parameter Spaces Using Multivariate Prediction at reposiTUm , opens an external URL in a new window
Croux, C., Filzmoser, P., & Fritz, H. (2011). Robust sparse principal component analysis (SM-2011-2).
| Robust sparse principal component analysis at reposiTUm , opens an external URL in a new window
Endel, F., Endel, G., Filzmoser, P., Weibold, B., & Katschnig, H. (2011). Health service record linkage in a situation of multiple social health insurance institutions: the case of Austria. SHIP Biennial Conference, St Andrews, EU.
| Health service record linkage in a situation of multiple social health insurance institutions: the case of Austria at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2011). Analyzing high-dimensional data, with application to chemometrics. University of Valladolid, Valladolid, EU.
| Analyzing high-dimensional data, with application to chemometrics at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2011). Finding relevant descriptors. Workshop “Molecular Descriptors,” Wien, Austria.
| Finding relevant descriptors at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2011). Multivariate statistics using R. University of Salatiga, Salatiga, Non-EU.
| Multivariate statistics using R at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2011). Regression and classification methods for high-dimensional data with application to chemometrics. Conferencias Statistical Robustness, Oviedo, EU.
| Regression and classification methods for high-dimensional data with application to chemometrics at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2011). Robust sparse principal component analysis. Statistische Tage 2011, Graz, Austria.
| Robust sparse principal component analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2011). Robust statistics: Concepts, methods, applications, and computation. SEAMS-GMU 2011 International Conference on Mathematics and Its Applications, Yogyakarta, Non-EU.
| Robust statistics: Concepts, methods, applications, and computation at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2011). Sparse multivariate methods for high-dimensional data. 7th International Symposium on Computer Applications and Chemometrics in Analytical Chemistry, Sümeg, EU.
| Sparse multivariate methods for high-dimensional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2011). Sparse regression and classification methods for high-dimensional data. University of Valladolid, Valladolid, EU.
| Sparse regression and classification methods for high-dimensional data at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2011). Robuste multivariate Methoden für die Analyse von Kompositionsdaten. Workshop TU Dresden - TU Wien, Dresden, EU.
| Robuste multivariate Methoden für die Analyse von Kompositionsdaten at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2011). Robust statistical analysis. In Compositional Data Analysis: Theory and Applications (pp. 59–72). John Wiley & Sons.
| Robust statistical analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Todorov, V. (2011). Review of robust multivariate statistical methods in high dimension (SM-2011-1).
| Review of robust multivariate statistical methods in high dimension at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Todorov, V. (2011). Review of robust multivariate statistical methods in high dimension. Analytica Chimica Acta, 705(1–2), 2–14. https://doi.org/10.1016/j.aca.2011.03.055, opens an external URL in a new window
| Review of robust multivariate statistical methods in high dimension at reposiTUm , opens an external URL in a new window
Filzmoser, P., Croux, C., & Fritz, H. (2011). Robust sparse principal component analysis based on projection-pursuit. International Conference on Robust Statistics in Valladolid, Spanien, EU.
| Robust sparse principal component analysis based on projection-pursuit at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., & Templ, M. (2011). Discriminant Analysis for Compositional Data and Robust Parameter Estimation. In Book of Abstracts of the Olomoucian Days of Applied Mathematics (p. 17).
| Discriminant Analysis for Compositional Data and Robust Parameter Estimation at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., & Templ, M. (2011). Robust compositional data analysis. In Proceedings of the 4th International Workshop on Compositional Data Analysis (p. 4).
| Robust compositional data analysis at reposiTUm , opens an external URL in a new window
Graf, M., Alfons, A., Bruch, C., Filzmoser, P., Hulliger, B., Lehtonen, R., Meindl, B., Münnich, R., Schoch, T., Templ, M., Valaste, M., Wenger, A., & Zins, S. (2011). State-of-the-art of indicators on poverty and social exclusion the Laeken indicators (Europ. Commission,FP7-SSH-2007-21732,WP1-D1.1).
| State-of-the-art of indicators on poverty and social exclusion the Laeken indicators at reposiTUm , opens an external URL in a new window
Gschwandtner, M., Filzmoser, P., Croux, C., & Haesbroeck, G. (2011). A robust approach to regularized discriminant analysis. Statistische Tage 2011, Graz, Austria.
| A robust approach to regularized discriminant analysis at reposiTUm , opens an external URL in a new window
Hron, K., & Filzmoser, P. (2011). Linear regression with compositional explanatory variables using the logratio approach. International Conference of Probability and Statistics, Smolenice, EU.
| Linear regression with compositional explanatory variables using the logratio approach at reposiTUm , opens an external URL in a new window
Hron, K., & Filzmoser, P. (2011). Mathematical elements in robust statistics for CoDa. Congress of the Spanish Royal Mathematical Society, Avila, EU.
| Mathematical elements in robust statistics for CoDa at reposiTUm , opens an external URL in a new window
Hron, K., Fiserová, E., Filzmoser, P., & Templ, M. (2011). On the Interpretation of Orthonormal Coordinates for Compositional Data with Applications. In Book of Abstracts of the Olomoucian Days of Applied Mathematics (p. 27).
| On the Interpretation of Orthonormal Coordinates for Compositional Data with Applications at reposiTUm , opens an external URL in a new window
Hron, K., Templ, M., & Filzmoser, P. (2011). Classical and robust imputation of missing values for compositional data using balances. In Proceedings of the 4th International Workshop on Compositional Data Analysis (p. 1).
| Classical and robust imputation of missing values for compositional data using balances at reposiTUm , opens an external URL in a new window
Huf, W., Kalcher, K., Pail, G., Friedrich, M.-E., Filzmoser, P., & Kasper, S. (2011). Meta-analysis: Fact or fiction? How to interpret meta-analyses. The World Journal of Biological Psychiatry, 12(3), 188–200. https://doi.org/10.3109/15622975.2010.551544, opens an external URL in a new window
| Meta-analysis: Fact or fiction? How to interpret meta-analyses at reposiTUm , opens an external URL in a new window
Hulliger, B., Alfons, A., Bruch, C., Filzmoser, P., Graf, M., Kolb, J.-P., Lehtonen, R., Lussmann, D., Meraner, A., Münnich, R., Myrskylä, M., Nedyalkova, D., Schoch, T., Templ, M., Valaste, M., Veijanen, A., & Zins, S. (2011). Report on the simulation results: Appendix (Europ. Commission,FP7-SSH-2007-21732,WP7-D7.1-App).
| Report on the simulation results: Appendix at reposiTUm , opens an external URL in a new window
Hulliger, B., Alfons, A., Bruch, C., Filzmoser, P., Graf, M., Kolb, J.-P., Lehtonen, R., Lussmann, D., Meraner, A., Münnich, R., Myrskylä, M., Nedyalkova, D., Schoch, T., Templ, M., Valaste, M., Veijanen, A., & Zins, S. (2011). Report on the simulation results (Europ. Commission,FP7-SSH-2007-21732,WP7-D7.1).
| Report on the simulation results at reposiTUm , opens an external URL in a new window
Hulliger, B., Alfons, A., Filzmoser, P., Meraner, A., Schoch, T., & Templ, M. (2011). R programmes for robust procedures including manual (Europ. Commission,FP7-SSH-2007-21732,WP4-D4.1).
| R programmes for robust procedures including manual at reposiTUm , opens an external URL in a new window
Hulliger, B., Alfons, A., Filzmoser, P., Meraner, A., Schoch, T., & Templ, M. (2011). Robust methodology for Laeken indicators (Europ. Commission,FP7-SSH-2007-21732,WP4-D4.2).
| Robust methodology for Laeken indicators at reposiTUm , opens an external URL in a new window
Hulliger, B., Schoch, T., Alfons, A., Holzer, J., Filzmoser, P., Meraner, A., & Templ, M. (2011). WP4: Robustness (Europ. Commission,FP7-SSH-2007-21732,WP7-D7.1-10).
| WP4: Robustness at reposiTUm , opens an external URL in a new window
Hulliger, B., Zechner, S., Templ, M., & Filzmoser, P. (2011). Evaluation Plots: Revision and extensions (Europ. Commission,FP7-SSH-2007-21732,WP8-D8.2-3).
| Evaluation Plots: Revision and extensions at reposiTUm , opens an external URL in a new window
Katschnig, H., Endel, G., Endel, F., Filzmoser, P., & Weibold, B. (2011). Identifying psychiatric patients’ pathways of care: linking service use data for psychiatric and non-psychiatric services for the total population of a province of Austria. SHIP Biennial Conference, St Andrews, EU.
| Identifying psychiatric patients' pathways of care: linking service use data for psychiatric and non-psychiatric services for the total population of a province of Austria at reposiTUm , opens an external URL in a new window
Katschnig, H., Endel, G., Endel, F., Filzmoser, P., & Weibold, B. (2011). Identifying psychiatric patients’ pathways of care by record linkage after pseudonymisation: linking inpatient and outpatient data for the total population of a province of Austria. In Psychiatrische Praxis. Society for Psychotherapy Research. https://doi.org/10.1055/s-0031-1277820, opens an external URL in a new window
| Identifying psychiatric patients' pathways of care by record linkage after pseudonymisation: linking inpatient and outpatient data for the total population of a province of Austria at reposiTUm , opens an external URL in a new window
Meraner, A., Filzmoser, P., & Templ, M. (2011). Robust methods for semi-continuous data (Europ. Commission,FP7-SSH-2007-21732,WP4-D4.2-12).
| Robust methods for semi-continuous data at reposiTUm , opens an external URL in a new window
Munnich, R., Zins, S., Alfons, A., Bruch, C., Filzmoser, P., Graf, M., Hulliger, B., Kolb, J.-P., Lehtonen, R., Lussmann, D., Meraner, A., Myrskylä, M., Nedyalkova, D., Schoch, T., Templ, M., Valaste, M., & Veijanen, A. (2011). Policy Recommendations and Methodological Report (Europ. Commission,FP7-SSH-2007-217322,WP6-D10-1).
| Policy Recommendations and Methodological Report at reposiTUm , opens an external URL in a new window
Neykov, N., Cizek, P., Filzmoser, P., & Neytchev, P. (2011). Robust quantile regression estimator through trimming. International Conference on Robust Statistics in Valladolid, Spanien, EU.
| Robust quantile regression estimator through trimming at reposiTUm , opens an external URL in a new window
Pascoal, C., Oliveira, M. R., Filzmoser, P., Pacheco, A., & Valadas, R. (2011). A new approach for variable selection in robust PCA, applied to anomaly detection in internet traffic flows. International Conference on Robust Statistics in Valladolid, Spanien, EU.
| A new approach for variable selection in robust PCA, applied to anomaly detection in internet traffic flows at reposiTUm , opens an external URL in a new window
Reimann, R., Birke, M., & Filzmoser, P. (2011). Data analysis for urban geochemical data. In C. C. Johnson, A. Demetriades, J. Locutura, & R. T. Ottesen (Eds.), Mapping the Chemical Environment of Urban Areas (pp. 99–115). John Wiley & Sons.
| Data analysis for urban geochemical data at reposiTUm , opens an external URL in a new window
Sarbu, A., Janauer, G., Schmidt-Mumm, U., Filzmoser, P., Smarandache, D., & Pascale, G. (2011). Characterisation of the potamal Danube River and the Delta: connectivity determines indicative macrophyte assemblages. Hydrobiologia, 671(1), 75–93.
| Characterisation of the potamal Danube River and the Delta: connectivity determines indicative macrophyte assemblages at reposiTUm , opens an external URL in a new window
Sucharová, J., Suchara, I., Reimann, C., Boyd, R., Filzmoser, P., & Englmaier, P. (2011). Spatial distribution of lead and lead isotopes in soil B-horizon, forest-floor humus, grass (Avenella flexuosa) and spruce (Picea abies) needles across the Czech Republic. Applied Geochemistry, 26(7), 1205–1214. https://doi.org/10.1016/j.apgeochem.2011.04.009, opens an external URL in a new window
| Spatial distribution of lead and lead isotopes in soil B-horizon, forest-floor humus, grass (Avenella flexuosa) and spruce (Picea abies) needles across the Czech Republic at reposiTUm , opens an external URL in a new window
Templ, M., Alfons, A., & Filzmoser, P. (2011). Diagnostic tools for missing values (Europ. Commission,FP7-SSH-2007-21732,WP8-D8.2-8).
| Diagnostic tools for missing values at reposiTUm , opens an external URL in a new window
Templ, M., Alfons, A., & Filzmoser, P. (2011). Robust semi-parametric estimation of economic and social indicators. 58th Session of the ISI Conference, Dublin, EU.
| Robust semi-parametric estimation of economic and social indicators at reposiTUm , opens an external URL in a new window
Templ, M., Alfons, A., Filzmoser, P., & Holzer, J. (2011). Estimation of Social Inclusion Indicators with Bounded Influence of Incomes by Tail Modeling. In Book of Abstracts of the Olomoucian Days of Applied Mathematics (p. 61).
| Estimation of Social Inclusion Indicators with Bounded Influence of Incomes by Tail Modeling at reposiTUm , opens an external URL in a new window
Templ, M., Alfons, A., Filzmoser, P., Graf, M., Hulliger, B., Kolb, J.-P., Lehtonen, R., Münnich, R., Nedyalkova, D., Schoch, T., Veijanen, A., & Zins, S. (2011). R packages plus manual (Europ. Commission,FP7-SSH-2007-21732,WP10-D10.3).
| R packages plus manual at reposiTUm , opens an external URL in a new window
Templ, M., Alfons, A., Kowarik, A., Meindl, B., Filzmoser, P., Hulliger, B., & Lussmann, D. (2011). Visualisation of indicators within the AMELI project. In Proceedings of the NTTS 2011 conference (p. 2).
| Visualisation of indicators within the AMELI project at reposiTUm , opens an external URL in a new window
Templ, M., Filzmoser, P., & Hron, K. (2011). Analysis of Compositional Data using Robust Methods. The R-Package robCompositions. In Proceedings of the Conference of European Statisticians, Work Session on Statistical Data Editing. CODAWORK’11, Girona, EU.
| Analysis of Compositional Data using Robust Methods. The R-Package robCompositions at reposiTUm , opens an external URL in a new window
Templ, M., Hron, K., & Filzmoser, P. (2011). Robust imputation for compositional data (Europ. Commission,FP7-SSH-2007-21732,WP4-D4.2-11).
| Robust imputation for compositional data at reposiTUm , opens an external URL in a new window
Templ, M., Hron, K., & Filzmoser, P. (2011). robCompositions: an R-package for robust statistical analysis of compositional data. In Compositional Data Analysis: Theory and Applications (pp. 341–355). John Wiley & Sons.
| robCompositions: an R-package for robust statistical analysis of compositional data at reposiTUm , opens an external URL in a new window
Templ, M., Hulliger, B., Alfons, A., Lussmann, D., & Filzmoser, P. (2011). Visualisation tools (Europ. Commission,FP7-SSH-2007-21732,WP8-D8.2).
| Visualisation tools at reposiTUm , opens an external URL in a new window
Templ, M., Kowarik, A., & Filzmoser, P. (2011). EM-based regression imputation using robust methods (Europ. Commission,FP7-SSH-2007-21732,WP4-D4.2-8).
| EM-based regression imputation using robust methods at reposiTUm , opens an external URL in a new window
Templ, M., Kowarik, A., & Filzmoser, P. (2011). Imputation of complex data with R-package VIM: traditional and new methods based on robust estimation. In Proceedings of the Conference of European Statisticians, Work Session on Statistical Data Editing (p. 10).
| Imputation of complex data with R-package VIM: traditional and new methods based on robust estimation at reposiTUm , opens an external URL in a new window
Templ, M., Kowarik, A., & Filzmoser, P. (2011). Iterative stepwise regression imputation using standard and robust methods. Computational Statistics & Data Analysis, 55(10), 2793–2806. https://doi.org/10.1016/j.csda.2011.04.012, opens an external URL in a new window
| Iterative stepwise regression imputation using standard and robust methods at reposiTUm , opens an external URL in a new window
Templ, M., Kowarik, A., Filzmoser, P., & Alfons, A. (2011). A computational and methodological framework for visualisation and imputation of missing values: the R-package VIM. Statistische Tage 2011, Graz, Austria.
| A computational and methodological framework for visualisation and imputation of missing values: the R-package VIM at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2011). Sparse and robust methods for discrimination in high dimensions. Statistische Tage 2011, Graz, Austria.
| Sparse and robust methods for discrimination in high dimensions at reposiTUm , opens an external URL in a new window
Todorov, V., Templ, M., & Filzmoser, P. (2011). Detection of multivariate outliers in business survey data with incomplete information. Advances in Data Analysis and Classification, 5(1), 37–56. https://doi.org/10.1007/s11634-010-0075-2, opens an external URL in a new window
| Detection of multivariate outliers in business survey data with incomplete information at reposiTUm , opens an external URL in a new window
Todorov, V., Templ, M., & Filzmoser, P. (2011). Software for multivariate outlier detection in survey data. In Proceedings of the Conference of European Statisticians, Work Session on Statistical Data Editing (p. 16).
| Software for multivariate outlier detection in survey data at reposiTUm , opens an external URL in a new window
Todorov, V., Trendafilov, N., & Filzmoser, P. (2011). Sparse methods for robust discrimination in high dimensions. International Conference on Robust Statistics in Valladolid, Spanien, EU.
| Sparse methods for robust discrimination in high dimensions at reposiTUm , opens an external URL in a new window
Treiblmaier, H., & Filzmoser, P. (2011). Benefits from using continuous rating scales in online survey research. In Proceedings of the International Conference on Information Systems (p. 13). Association for Information Systems.
| Benefits from using continuous rating scales in online survey research at reposiTUm , opens an external URL in a new window
Varmuza, K., Engrand, C., Filzmoser, P., Hilchenbach, M., Kissel, J., Krüger, H., Silén, J., & Trieloff, M. (2011). Random projection for dimensionality reduction-Applied to time-of-flight secondary ion mass spectrometry data. Analytica Chimica Acta, 705(1–2), 48–55. https://doi.org/10.1016/j.aca.2011.03.031, opens an external URL in a new window
| Random projection for dimensionality reduction-Applied to time-of-flight secondary ion mass spectrometry data at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., & Liebmann, B. (2011). Repeated double cross validation for classification models. In Conferentia Chemometrica 2011. Conferentia Chemometrica 2011, Sümeg, Ungarn, EU.
| Repeated double cross validation for classification models at reposiTUm , opens an external URL in a new window

Alfons, A., & Filzmoser, P. (2010). Robust model selection in the social sciences. In Programme and Abstracts: 4th CSDA International Conference on Computational and Financial Econometrics (p. 63).
| Robust model selection in the social sciences at reposiTUm , opens an external URL in a new window
Alfons, A., Kraft, S., Templ, M., & Filzmoser, P. (2010). Simulation of synthetic population data for household surveys with application to EU-SILC (CS-2010-1).
| Simulation of synthetic population data for household surveys with application to EU-SILC at reposiTUm , opens an external URL in a new window
Alfons, A., Kraft, S., Templ, M., & Filzmoser, P. (2010). Simulation of population data for complex household surveys. In Abstracts of the International Conference on Indicators and Survey Methodology (p. 13).
| Simulation of population data for complex household surveys at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2010). Application of the R package simFrame for statistical simulation to EU-SILC. 4th AMELI Meeting, Wien, Austria.
| Application of the R package simFrame for statistical simulation to EU-SILC at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2010). Pareto tail modeling for social inclusion indicators. 6th AMELI Meeting, Trier, EU.
| Pareto tail modeling for social inclusion indicators at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2010). Simulation of EU-SILC population data: using the R package simPopulation (CS-2010-5).
| Simulation of EU-SILC population data: using the R package simPopulation at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2010). Text Von Andi. AMELI Meeting in Wien, Wien, Austria.
| Text Von Andi at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2010). An object-oriented framework for statistical simulation: The R Package simFrame. Journal of Statistical Software, 37(3), 1–36.
| An object-oriented framework for statistical simulation: The R Package simFrame at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2010). Contamination models in the R package simFrame for statistical simulation. In S. Aivazian, P. Filzmoser, & Y. Kharin (Eds.), Proceedings of the Ninth International Conference on Computer Data Analysis and Modeling (pp. 178–181).
| Contamination models in the R package simFrame for statistical simulation at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2010). Exploring Microdata with Missing Information. In Abstracts of the Workshop on Exploratory Data Analysis and Visualization (p. 11).
| Exploring Microdata with Missing Information at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2010). The R package simFrame: An object-oriented approach towards simulation studies in statistics. In Abstracts of Contributed Presentations (p. 13).
| The R package simFrame: An object-oriented approach towards simulation studies in statistics at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., Filzmoser, P., Holzer, J., & Gonzalez-Rodriguez, G. (2010). A comparison of robust methods for Pareto tail modeling in the case of Laeken indicators. In C. Borgelt, G. Gonzalez-Rodriguez, W. Trutschnig, M. A. Lubiano, M. A. Gil, P. Grzegorzewski, & O. Hryniewicz (Eds.), Combining Soft Computing and Statistical Methods in Data Analysis (pp. 17–24).
| A comparison of robust methods for Pareto tail modeling in the case of Laeken indicators at reposiTUm , opens an external URL in a new window
Boeheim, K., Pock, S.-M., Schloegel, M., & Filzmoser, P. (2010). Active Middle Ear Implant Compared With Open-Fit Hearing Aid in Sloping High-Frequency Sensorineural Hearing Loss. Otology and Neurotology, 31(3), 424–429.
| Active Middle Ear Implant Compared With Open-Fit Hearing Aid in Sloping High-Frequency Sensorineural Hearing Loss at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2010). Robust multivariate methods for compositional data. DAGStat 2010, Dortmund, EU.
| Robust multivariate methods for compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2010). Robust multivariate methods for high-dimensional data. Chemometrics in Analytical Chemistry (CAC 2010), Antwerpen, EU.
| Robust multivariate methods for high-dimensional data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2010). The “chemometrics” package in R - Application in multivariate calibration and classification. Chemometrics Workshop, Wien, Austria.
| The "chemometrics" package in R - Application in multivariate calibration and classification at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2010). Soft methods in robust statistics. In C. Borgelt, G. Gonzalez-Rodriguez, W. Trutschnig, M. A. Lubiano, M. A. Gil, P. Grzegorzewski, & O. Hryniewicz (Eds.), Combining Soft Computing and Statistical Methods in Data Analysis (pp. 273–280).
| Soft methods in robust statistics at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Horn, K. (2010). Multivariate outlier detection with compositional data. In S. Aivazian, P. Filzmoser, & Y. Kharin (Eds.), Proceedings of the Ninth International Conference on Computer Data Analysis and Modeling (pp. 45–52).
| Multivariate outlier detection with compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Horn, K. (2010). Robust methods for compositional data. In G. Saporta & Y. Lechevallier (Eds.), Proceedings in Computational Statistics (pp. 79–88).
| Robust methods for compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Templ, M. (2010). Data Analysis with Robust Statistical Methods. In Abstracts of the Workshop on Exploratory Data Analysis and Visualization (p. 17).
| Data Analysis with Robust Statistical Methods at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., & Reimann, R. (2010). The bivariate statistical analysis of environmental (compositional) data. Science of the Total Environment, 408, 4230–4238.
| The bivariate statistical analysis of environmental (compositional) data at reposiTUm , opens an external URL in a new window
Fritz, H., Filzmoser, P., & Croux, C. (2010). A comparison of algorithms for the multivariate L1-median (CS-2010-4).
| A comparison of algorithms for the multivariate L1-median at reposiTUm , opens an external URL in a new window
Hron, K., & Filzmoser, P. (2010). Robust regression for compositional data. International Conference on Robust Statistics, Parma, EU.
| Robust regression for compositional data at reposiTUm , opens an external URL in a new window
Hron, K., & Filzmoser, P. (2010). Elements of robust regression for data with absolute and relative information. In C. Borgelt, G. Gonzalez-Rodriguez, W. Trutschnig, M. A. Lubiano, M. A. Gil, P. Grzegorzewski, & O. Hryniewicz (Eds.), Combining Soft Computing and Statistical Methods in Data Analysis (pp. 329–335).
| Elements of robust regression for data with absolute and relative information at reposiTUm , opens an external URL in a new window
Hron, K., Filzmoser, P., & Templ, M. (2010). Classical and robust simple random sampling for compositional data. In Abstracts of the International Conference on Indicators and Survey Methodology (p. 33).
| Classical and robust simple random sampling for compositional data at reposiTUm , opens an external URL in a new window
Hron, K., Templ, M., & Filzmoser, P. (2010). Exploratory compositional data analysis using the R-package robCompositions. In S. Aivazian, P. Filzmoser, & Y. Kharin (Eds.), Proceedings of the Ninth International Conference Data Analysis and Modeling (pp. 179–186).
| Exploratory compositional data analysis using the R-package robCompositions at reposiTUm , opens an external URL in a new window
Hron, K., Templ, M., & Filzmoser, P. (2010). Imputation of missing values for compositional data using classical and robust methods. Computational Statistics & Data Analysis, 54, 3095–3107.
| Imputation of missing values for compositional data using classical and robust methods at reposiTUm , opens an external URL in a new window
Karacsony, Z., & Filzmoser, P. (2010). Asymptotic normality of kernel type regression estimators for random fields. Journal of Statistical Planning and Inference, 140, 872–886.
| Asymptotic normality of kernel type regression estimators for random fields at reposiTUm , opens an external URL in a new window
Katschnig, H., Endel, G., Endel, F., Filzmoser, P., & Weibold, B. (2010). Identifying psychiatric patients’ pathways through the health care system by record linkage after pseudonymisation. 26th PCSI annual conference, München, EU.
| Identifying psychiatric patients' pathways through the health care system by record linkage after pseudonymisation at reposiTUm , opens an external URL in a new window
Kehrer, J., Filzmoser, P., & Hauser, H. (2010). Brushing Moments in Interactive Visual Analysis. Eurograhics Digital Library, 29(3), 10.
| Brushing Moments in Interactive Visual Analysis at reposiTUm , opens an external URL in a new window
Liebmann, B., Filzmoser, P., & Varmuza, K. (2010). Robust and classical PLS regression compared. Journal of Chemometrics, 24(3–4), 111–120. https://doi.org/10.1002/cem.1279, opens an external URL in a new window
| Robust and classical PLS regression compared at reposiTUm , opens an external URL in a new window
Meraner, A., Templ, M., & Filzmoser, P. (2010). Outlier Detection for Semi-continuous Variables. AMELI Meeting in Wien, Wien, Austria.
| Outlier Detection for Semi-continuous Variables at reposiTUm , opens an external URL in a new window
Neykov, N., Filzmoser, P., & Neytchev, P. (2010). Robust joint modeling of the mean and dispersion through trimming. International Conference on Robust Statistics, Parma, EU.
| Robust joint modeling of the mean and dispersion through trimming at reposiTUm , opens an external URL in a new window
Pfeffer, N., Eisl, A., Endel, F., Filzmoser, P., Scholler, C., & Weisser, A. (2010). Identification of diagnose-related procedure bundles in outpatient care using statistical methods. 26th PCSI annual conference, München, EU.
| Identification of diagnose-related procedure bundles in outpatient care using statistical methods at reposiTUm , opens an external URL in a new window
Reimann, C., Birke, M., & Filzmoser, P. (2010). Bottled drinking water: Water contamination from bottle materials (glass, hard PET, soft PET), the influence of colour and acidification. Applied Geochemistry, 25, 1030–1046.
| Bottled drinking water: Water contamination from bottle materials (glass, hard PET, soft PET), the influence of colour and acidification at reposiTUm , opens an external URL in a new window
Reimann, C., Birke, M., & Filzmoser, P. (2010). Reply to the comment “Bottled drinking water: Water contamination from bottle materials (glass, hard PET, soft PET), the influence of colour and acidification” by Hayo Müller-Simon. Applied Geochemistry, 25, 1464–1465.
| Reply to the comment "Bottled drinking water: Water contamination from bottle materials (glass, hard PET, soft PET), the influence of colour and acidification" by Hayo Müller-Simon at reposiTUm , opens an external URL in a new window
Templ, M., Hron, K., & Filzmoser, P. (2010). robCompositions: An R-package for robust statistical analysis of compositional data. In Abstracts of Contributed Presentations (p. 161).
| robCompositions: An R-package for robust statistical analysis of compositional data at reposiTUm , opens an external URL in a new window
Templ, M., Kovarik, A., Filzmoser, P., & Alfons, A. (2010). Iterative imputation of complex survey data using robust methods. In Abstracts of the International Conference on Indicators and Survey Methodology (p. 51).
| Iterative imputation of complex survey data using robust methods at reposiTUm , opens an external URL in a new window
Templ, M., Kowarik, A., & Filzmoser, P. (2010). EM-based stepwise regression imputation using standard and robust methods (CS-2010-3).
| EM-based stepwise regression imputation using standard and robust methods at reposiTUm , opens an external URL in a new window
Templ, M., Kowarik, A., & Filzmoser, P. (2010). IRMI: An open-source solution for imputation of complex data using robust methods. European Conference on Quality in Official Statistics 2010, Helsinki, EU.
| IRMI: An open-source solution for imputation of complex data using robust methods at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2010). Robust discrimination in high dimensions. International Conference on Robust Statistics, Parma, EU.
| Robust discrimination in high dimensions at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2010). Robust statistic for the one-way MANOVA. Computational Statistics & Data Analysis, 54, 37–48.
| Robust statistic for the one-way MANOVA at reposiTUm , opens an external URL in a new window
Treiblmaier, H., & Filzmoser, P. (2010). Exploratory factor analysis revisited: How robust methods support the detection of hidden multivariate data structures in IS research. Information and Management, 47, 197–207.
| Exploratory factor analysis revisited: How robust methods support the detection of hidden multivariate data structures in IS research at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., & Dehmer, M. (2010). Statistical evaluation of molecular descriptors used in quantitative-structure-activity relationships. In Programme and Abstracts (p. 55).
| Statistical evaluation of molecular descriptors used in quantitative-structure-activity relationships at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., & Liebmann, B. (2010). Random projection experiments with chemometric data. Journal of Chemometrics, 24(3–4), 209–217. https://doi.org/10.1002/cem.1295, opens an external URL in a new window
| Random projection experiments with chemometric data at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., Hilchenbach, M., Kissel, J., Krüger, H., & Silèn, J. (2010). Random projection for dimensionality reduction - applied to TOF-SIMS data relevant for future experiments near a comet. In CAC 2010 Book of Abstracts (p. 277).
| Random projection for dimensionality reduction - applied to TOF-SIMS data relevant for future experiments near a comet at reposiTUm , opens an external URL in a new window
Weisser, A., Endel, F., Endel, G., & Filzmoser, P. (2010). Results of the project ATC-ICD. 26th PCSI annual conference, München, EU.
| Results of the project ATC-ICD at reposiTUm , opens an external URL in a new window
Wieser, R., Filzmoser, H., Filzmoser, P., Alfons, A., Baaske, W. E., & Mader, W. (2010). How to improve the Quality of Life in Central European Municipalities. International Conference on Indicators and Survey Methodology, Wien, Austria.
| How to improve the Quality of Life in Central European Municipalities at reposiTUm , opens an external URL in a new window
Zechner, S., Filzmoser, P., Templ, M., & Alfons, A. (2010). Visualization of Indicators in R with application to EUSILC. 4th AMELI Meeting, Wien, Austria.
| Visualization of Indicators in R with application to EUSILC at reposiTUm , opens an external URL in a new window

Alfons, A., Filzmoser, P., & Templ, M. (2009). Summary of the State-of-the-Art in Visualization of the European Laeken Indicators (AMELI Project Deliverable 8.1, Part 3).
| Summary of the State-of-the-Art in Visualization of the European Laeken Indicators at reposiTUm , opens an external URL in a new window
Alfons, A., Filzmoser, P., Hulliger, B., Meindl, B., Schoch, T., & Templ, M. (2009). State-of-the-art in visualization of indicators in survey statistics (CS-2009-4).
| State-of-the-art in visualization of indicators in survey statistics at reposiTUm , opens an external URL in a new window
Alfons, A., Filzmoser, P., Kraft, S., & Templ, M. (2009). Generation of synthetic EU-SILC data and simulation (CS-2009-5).
| Generation of synthetic EU-SILC data and simulation at reposiTUm , opens an external URL in a new window
Alfons, A., Filzmoser, P., Kraft, S., & Templ, M. (2009). Intermediate report on the data generation mechanism and of the design of the simulation study (AMELI Project Deliverable 6.1).
| Intermediate report on the data generation mechanism and of the design of the simulation study at reposiTUm , opens an external URL in a new window
Alfons, A., Filzmoser, P., Kraft, S., & Templ, M. (2009). Progress Report WP6-Simulation (AMELI Project Deliverable 6.1, Part 2).
| Progress Report WP6-Simulation at reposiTUm , opens an external URL in a new window
Alfons, A., Filzmoser, P., Kraft, S., & Templ, M. (2009). Summary of the state-of-the-art in simulation in survey statistics (AMELI Project Deliverable 6.1, Part1).
| Summary of the state-of-the-art in simulation in survey statistics at reposiTUm , opens an external URL in a new window
Alfons, A., Kraft, S., Filzmoser, P., & Templ, M. (2009). Progress report on simulation and synthetic data generation for EU-SILC data (CS-2009-6).
| Progress report on simulation and synthetic data generation for EU-SILC data at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2009). State-of-the-Art and recent developments in Visualisation of Missing Values and Indicators. 3rd AMELI meeting, Olten, Non-EU.
| State-of-the-Art and recent developments in Visualisation of Missing Values and Indicators at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2009). simFrame: An object-oriented framework for statistical simulation (CS-2009-1).
| simFrame: An object-oriented framework for statistical simulation at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2009). On the influence of imputation methods on Laeken indicators: simulations and recommendations. In Proceedings of the Conference of European Statisticians (p. 9).
| On the influence of imputation methods on Laeken indicators: simulations and recommendations at reposiTUm , opens an external URL in a new window
Baaske, W. E., Filzmoser, P., Mader, W., & Wieser, R. (2009). Agriculture as a success factor for municipalities. In Jahrbuch der Österreichischen Gesellschaft für Agrarökonomie (pp. 21–30). Facultas Verlags- und Buchhandels AG.
| Agriculture as a success factor for municipalities at reposiTUm , opens an external URL in a new window
Boubela, R., Filzmoser, P., & Piringer, H. (2009). Integrating R into the InfoVis System Visplore. useR! 2009, Rennes, EU.
| Integrating R into the InfoVis System Visplore at reposiTUm , opens an external URL in a new window
Boubela, R., Filzmoser, P., & Piringer, H. (2009). Visplore and R: a symbiosis of powerfull visualization and statistical processing. Young Statisticians Meeting, Piran, Slowenien, EU.
| Visplore and R: a symbiosis of powerfull visualization and statistical processing at reposiTUm , opens an external URL in a new window
Filzmoser, H., & Filzmoser, P. (2009). ErfolgsVision: Ergebnisdarstellung. Workshop: Erfolgsfaktoren für Gemeinden, Bad Zell, Austria.
| ErfolgsVision: Ergebnisdarstellung at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2009). Applied Environmental Statistics with Focus on Exploratory Data Analysis. IASC-ERS Summer School on Computational Aspects in Environmental Statistics, Pamporovo, EU.
| Applied Environmental Statistics with Focus on Exploratory Data Analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2009). ErfolgsVision: Statistische Methodik. Workshop: Erfolgsfaktoren für Gemeinden, Bad Zell, Austria.
| ErfolgsVision: Statistische Methodik at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2009). Exploratory Data Analysis und Visualization with R. Workshop “R” in Teaching and Empirical Research, Wien, Austria.
| Exploratory Data Analysis und Visualization with R at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2009). Robust Exploratory Factor Analysis as a Reliable Statistical Tool in IS Research. KIMEP International Research Conference, Almaty, Non-EU.
| Robust Exploratory Factor Analysis as a Reliable Statistical Tool in IS Research at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2009). Robust Statistics: Concepts, Methods, Applications, and Software. COST Spring School, Mieres, EU.
| Robust Statistics: Concepts, Methods, Applications, and Software at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2009). Statistical Practices for Environmental Monitoring. 57th Session of the International Statistical Institute, Durban, Non-EU.
| Statistical Practices for Environmental Monitoring at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2009). Statistische Analyse von Kompositionsdaten. Institut für Statistik, Graz, Austria.
| Statistische Analyse von Kompositionsdaten at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2009). Invariant co-ordinate selection (Discussion on this paper). Journal of the Royal Statistical Society, 71(3), 549–592.
| Invariant co-ordinate selection (Discussion on this paper) at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2009). Correlation Analysis for Compositional Data. Mathematical Geosciences, 41, 905–919.
| Correlation Analysis for Compositional Data at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2009). Robust Factor Analysis. In Abstracts of the International Conference on Robust Statistics (pp. 51–52).
| Robust Factor Analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2009). Univariate statistical analysis of environmental (compositional) data: Problems and possibilities. Science of the Total Environment, 407, 6100–6108.
| Univariate statistical analysis of environmental (compositional) data: Problems and possibilities at reposiTUm , opens an external URL in a new window
Filzmoser, P., Fritz, H., Horn, K., & Templ, M. (2009). The estimation of missing data in presence of outliers: computational aspects. In Abstracts of the Third International Conference on Computational and Financial Econometrics (CFE 09) and Second Workshop of the ERCIM Working Group on Computing & Statistics (ERCIM 09) (p. 29).
| The estimation of missing data in presence of outliers: computational aspects at reposiTUm , opens an external URL in a new window
Filzmoser, P., Gieber, H., Liebmann, B., & Varmuza, K. (2009). Classification Methods Applied to Chemical Data Using the R Library “chemometrics.” In Conferentia Chemometrica 2009 Abstract Book. Conferentia Chemometrica 2009, Siofok,Ungarn, EU.
| Classification Methods Applied to Chemical Data Using the R Library "chemometrics" at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., & Reimann, C. (2009). Univariate statistical analysis of environmental data: Problems and possibilities (SM-2009-2).
| Univariate statistical analysis of environmental data: Problems and possibilities at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., & Reimann, C. (2009). Principal component analysis for compositional data with outliers. Environmetrics, 20, 621–632.
| Principal component analysis for compositional data with outliers at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., & Templ, M. (2009). Discriminant analysis for compositional data and robust parameter estimation (SM-2009-3).
| Discriminant analysis for compositional data and robust parameter estimation at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., Reimann, C., & Garrett, R. G. (2009). Robust factor analysis for compositional data. Computers and Geosciences, 35, 1854–1861.
| Robust factor analysis for compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P., Liebmann, B., & Varmuza, K. (2009). Repeated double cross validation. Journal of Chemometrics, 23, 160–171.
| Repeated double cross validation at reposiTUm , opens an external URL in a new window
Filzmoser, P., Liebmann, B., & Varmuza, K. (2009). Repeated double cross validation. In 11#^{th} Scandinavian Symposium on Chemometrics SSC11 - Book of Abstracts (p. 39).
| Repeated double cross validation at reposiTUm , opens an external URL in a new window
Filzmoser, P., Serneels, S., Maronna, R., & Van Espen, P. J. (2009). Robust Multivariate Methods in Chemometrics. In S. D. Brown, R. Tauler, & B. Walczak (Eds.), Comprehensive Chemometrics: Chemical and Biochemical Data Analysis (pp. 663–722). Elsevier.
| Robust Multivariate Methods in Chemometrics at reposiTUm , opens an external URL in a new window
Hron, K., & Filzmoser, P. (2009). A Robust Biplot for Compositional Data. In Abstracts of the International Conference on Robust Statistics (pp. 70–71).
| A Robust Biplot for Compositional Data at reposiTUm , opens an external URL in a new window
Kraft, S., Filzmoser, P., & Templ, M. (2009). Simulation of a Population for the European Living and Income Conditions Survey. 3rd AMELI meeting, Olten, Non-EU.
| Simulation of a Population for the European Living and Income Conditions Survey at reposiTUm , opens an external URL in a new window
Liebmann, B., Filzmoser, P., & Varmuza, K. (2009). Robust and classical PLS regression compared (CS-2009-8).
| Robust and classical PLS regression compared at reposiTUm , opens an external URL in a new window
Liebmann, B., Filzmoser, P., Friedl, A., & Varmuza, K. (2009). Classical and Robust PLS Regression compared by Repeated Double Cross Validation. In Conferentia Chemometrica 2009 Abstract Book. Conferentia Chemometrica 2009, Siofok,Ungarn, EU.
| Classical and Robust PLS Regression compared by Repeated Double Cross Validation at reposiTUm , opens an external URL in a new window
Neykov, N., Filzmoser, P., & Neytchev, P. (2009). Statistical Estimators based on Trimming. In Abstracts of the International Conference on Robust Statistics (p. 112).
| Statistical Estimators based on Trimming at reposiTUm , opens an external URL in a new window
Templ, M., Alfons, A., & Filzmoser, P. (2009). Tools for visualising data and aggregated information (CS-2009-3).
| Tools for visualising data and aggregated information at reposiTUm , opens an external URL in a new window
Templ, M., Alfons, A., & Filzmoser, P. (2009). Exploring the multivariate structure of missing values using the R package VIM. In Abstracts of the 5th R useR Conference (p. 194).
| Exploring the multivariate structure of missing values using the R package VIM at reposiTUm , opens an external URL in a new window
Templ, M., Filzmoser, P., & Hron, K. (2009). Imputation of item non-responses in compositional data using robust methods. In Proceedings of the Conference of European Statisticians (p. 11).
| Imputation of item non-responses in compositional data using robust methods at reposiTUm , opens an external URL in a new window
Templ, M., Filzmoser, P., & Hron, K. (2009). Missing Values in Compositional Data: Imputation and Diagnostics. In Abstracts of the 6th International Conference on Computational Management Science (p. 16).
| Missing Values in Compositional Data: Imputation and Diagnostics at reposiTUm , opens an external URL in a new window
Templ, M., Filzmoser, P., & Hron, K. (2009). Robust Imputation of Missing Values in Compositional Data Using the R-package robCompositions. In Proceedings of the NTTS Conference. NTTS Conference, Brüssel, EU.
| Robust Imputation of Missing Values in Compositional Data Using the R-package robCompositions at reposiTUm , opens an external URL in a new window
Templ, M., Filzmoser, P., & Hron, K. (2009). Robustness for Compositional Data Using the R Package robCompositions. In Abstracts of the International Conference in Robust Statistics (pp. 146–147).
| Robustness for Compositional Data Using the R Package robCompositions at reposiTUm , opens an external URL in a new window
Templ, M., Holzer, J., Filzmoser, P., & Alfons, A. (2009). Robust methods for the estimation of selected Laeken indicators. 3rd AMELI meeting, Olten, Non-EU.
| Robust methods for the estimation of selected Laeken indicators at reposiTUm , opens an external URL in a new window
Templ, M., Kowarik, A., & Filzmoser, P. (2009). Iterative robust model-based Imputation of complex data. In Abstracts of the Third International Conference on Computational and Financial Econometrics (CFE 09) and Second Workshop of the ERCIM Working Group on Computing & Statistics (ERCIM) 09 (p. 29).
| Iterative robust model-based Imputation of complex data at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2009). An object-oriented framework for robust multivariate analysis (CS-2009-7).
| An object-oriented framework for robust multivariate analysis at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2009). Multivariate Robust Statistics - Methods and Computation. Südwestdeutscher Verlag für Hochschulschriften.
| Multivariate Robust Statistics - Methods and Computation at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2009). An Object-Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47.
| An Object-Oriented Framework for Robust Multivariate Analysis at reposiTUm , opens an external URL in a new window
Todorov, V., Templ, M., & Filzmoser, P. (2009). Outlier detection in survey data using robust methods. In Proceedings of the Conference of European Statisticians (p. 11).
| Outlier detection in survey data using robust methods at reposiTUm , opens an external URL in a new window
Todorov, V., Templ, M., & Filzmoser, P. (2009). Robust Outlier Detection in Survey Data. In Abstracts of the International Conference in Robust Statistics (pp. 148–149).
| Robust Outlier Detection in Survey Data at reposiTUm , opens an external URL in a new window
Treiblmaier, H., & Filzmoser, P. (2009). Benefits from using continuous rating scales in online survey research (SM-2009-4).
| Benefits from using continuous rating scales in online survey research at reposiTUm , opens an external URL in a new window
Treiblmaier, H., & Filzmoser, P. (2009). Exploratory factor analysis revisited: How robust methods support the detection of hidden multivariate data structures in IS research (SM-2009-5).
| Exploratory factor analysis revisited: How robust methods support the detection of hidden multivariate data structures in IS research at reposiTUm , opens an external URL in a new window
Varmuza, K., & Filzmoser, P. (2009). Introduction to Multivariate Statistical Analysis in Chemometrics. CRC Press.
| Introduction to Multivariate Statistical Analysis in Chemometrics at reposiTUm , opens an external URL in a new window
Varmuza, K., Filzmoser, P., & Liebmann, B. (2009). Random Projection and Projection Pursuit Based PCA Applied to Chemical Data. In Conferentia Chemometrica 2009 Abstract Book. Conferentia Chemometrica 2009, Siofok,Ungarn, EU.
| Random Projection and Projection Pursuit Based PCA Applied to Chemical Data at reposiTUm , opens an external URL in a new window
Vezzoli, G., Hron, K., & Filzmoser, P. (2009). A Statistical Approach to the Reconstruction of Pleistocene Drainage of the Po River Basin. In Abstracts of the International Conference on Robust Statistics (pp. 155–156).
| A Statistical Approach to the Reconstruction of Pleistocene Drainage of the Po River Basin at reposiTUm , opens an external URL in a new window

Alfons, A., Baaske, W. E., Filzmoser, P., Mader, W., & Wieser, R. (2008). A context-sensitive method for robust model selection with application to analysing success factors of communities (CS-2008-6).
| A context-sensitive method for robust model selection with application to analysing success factors of communities at reposiTUm , opens an external URL in a new window
Alfons, A., Kraft, S., Templ, M., & Filzmoser, P. (2008). Analyse und Visualisierung von EU-SILC Daten in R. In Abstracts of the Workshop TU Wien/TU Dresden (p. 6).
| Analyse und Visualisierung von EU-SILC Daten in R at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2008). Complex Survey Data Sets: Visualization of Missing Values in R. Young European Statisticians Workshop, Eindhoven, EU.
| Complex Survey Data Sets: Visualization of Missing Values in R at reposiTUm , opens an external URL in a new window
Alfons, A., Templ, M., & Filzmoser, P. (2008). Visualization Software for EU-SILC Data and Laeken Indicators. AMELI Meeting, Wiesbaden, EU.
| Visualization Software for EU-SILC Data and Laeken Indicators at reposiTUm , opens an external URL in a new window
Baaske, W. E., Filzmoser, P., Mader, W., & Wieser, R. (2008). Landwirtschaft als Erfolgsfaktor für Kommunen? Ergebnisse aus Bevölkerungsbefragungen in Bürgerbeteiligungsprozessen. ÖGA-Jahrestagung 2008, Wien, EU.
| Landwirtschaft als Erfolgsfaktor für Kommunen? Ergebnisse aus Bevölkerungsbefragungen in Bürgerbeteiligungsprozessen at reposiTUm , opens an external URL in a new window
Boubela, R., Filzmoser, P., & Piringer, H. (2008). Integration der Statistiksoftware R in die Visualisierungssoftware Bulk Analyzer zur interaktiven Datenanalyse. In Abstracts of the Workshop TU Wien/TU Dresden (p. 8).
| Integration der Statistiksoftware R in die Visualisierungssoftware Bulk Analyzer zur interaktiven Datenanalyse at reposiTUm , opens an external URL in a new window
Croux, C., Filzmoser, P., & Joossens, K. (2008). Classification efficiencies for robust linear discriminant analysis. Statistica Sinica, 18, 581–599.
| Classification efficiencies for robust linear discriminant analysis at reposiTUm , opens an external URL in a new window
Dutter, R., Filzmoser, P., & Kharin, Y. (Eds.). (2008). Special Issue on the Eighth International Conference Computer Data Analysis and Modeling. Österreichische Statistische Gesellschaft.
| Special Issue on the Eighth International Conference Computer Data Analysis and Modeling at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2008). Defining background: Which statistical method ? Outliers versus extreme values. Eurosoil 2008, Wien, Austria.
| Defining background: Which statistical method ? Outliers versus extreme values at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2008). Linear and nonlinear methods for regression and classification and applications in R (CS-2008-3).
| Linear and nonlinear methods for regression and classification and applications in R at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2008). Outlier Identification and Robust PCA for Compositional Data. Seminar of the Statistics Department, Belarusian State University, Minsk, Non-EU.
| Outlier Identification and Robust PCA for Compositional Data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2008). Robust fitting of mixtures: The approach based on the Trimmed Likelihood Estimator. The 32nd Annual Conference of the German Classification Society, Hamburg, EU.
| Robust fitting of mixtures: The approach based on the Trimmed Likelihood Estimator at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2008). Robust statistics: a clever approach for using the useful data information. 4th International Symposium on Computer Applications and Chemometrics in Analytical Chemistry, Balatonalmadi, EU.
| Robust statistics: a clever approach for using the useful data information at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2008). Correlation analysis for compositional data (SM-2008-2).
| Correlation analysis for compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2008). Outlier Detection for Compositional Data Using Robust Methods. Mathematical Geosciences, 40(3), 233–248.
| Outlier Detection for Compositional Data Using Robust Methods at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2008). Robust Statistical Methods for Compositional Data. In Abstracts of the International Conference On Robust Statistics (p. 37).
| Robust Statistical Methods for Compositional Data at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., Reimann, C., & Garrett, R. G. (2008). Robust factor analysis for compositional data (SM-2008-3).
| Robust factor analysis for compositional data at reposiTUm , opens an external URL in a new window
Filzmoser, P., Liebmann, B., & Varmuza, K. (2008). Repeated double cross validation (CS-2008-4).
| Repeated double cross validation at reposiTUm , opens an external URL in a new window
Filzmoser, P., Maronna, R., & Werner, M. (2008). Outlier identification in high dimensions. Computational Statistics & Data Analysis, 52, 1694–1711.
| Outlier identification in high dimensions at reposiTUm , opens an external URL in a new window
Filzmoser, P., Ruiz-Gazen, A., Thomas-Agnan, C., & Reimann, C. (2008). Tools for local multivariate outlier detection. 1st Workshop of the ERCIM Working Group on Computing and Statistics, Neuchatel, Non-EU.
| Tools for local multivariate outlier detection at reposiTUm , opens an external URL in a new window
Fritz, H., & Filzmoser, P. (2008). Plausibility of Databases and the Relation to Imputation Methods. VDM Verlag Dr. Müller.
| Plausibility of Databases and the Relation to Imputation Methods at reposiTUm , opens an external URL in a new window
Germ, M., Urbanc-Bercic, O., Janauer, G., Filzmoser, P., Exler, N., & Gaberscik, A. (2008). Macrophyte distribution pattern in the Krka River--the role of habitat quality. Large Rivers, 18(1-2), 145–155.
| Macrophyte distribution pattern in the Krka River--the role of habitat quality at reposiTUm , opens an external URL in a new window
Hron, K., & Filzmoser, P. (2008). Robuste Biplots für Kompositionsdaten. In Abstracts of the Workshop TU Wien/TU Dresden (p. 16).
| Robuste Biplots für Kompositionsdaten at reposiTUm , opens an external URL in a new window
Hron, K., Templ, M., & Filzmoser, P. (2008). Imputation of missing values for compositional data using classical and robust methods (SM-2008-4).
| Imputation of missing values for compositional data using classical and robust methods at reposiTUm , opens an external URL in a new window
Hron, K., Templ, M., & Filzmoser, P. (2008). A Robust Approach for Dealing with Missing Values in Compositional Data. In Abstracts of the International Conference on Robust Statistics 2008 (pp. 48–49).
| A Robust Approach for Dealing with Missing Values in Compositional Data at reposiTUm , opens an external URL in a new window
Karacsony, Z., & Filzmoser, P. (2008). Asymptotic normality of kernel type regression estimators for random fields (MS-2008-1).
| Asymptotic normality of kernel type regression estimators for random fields at reposiTUm , opens an external URL in a new window
Kraft, S., Templ, M., & Filzmoser, P. (2008). Simulation. AMELI Meeting, Wiesbaden, EU.
| Simulation at reposiTUm , opens an external URL in a new window
Neykov, N., Filzmoser, P., & Neytchev, P. (2008). Recent developments in robust fitting of mixtures. In Abstracts of the International Conference on Robust Statistics (p. 74).
| Recent developments in robust fitting of mixtures at reposiTUm , opens an external URL in a new window
Reimann, C., & Filzmoser, P. (2008). Principal Component Analysis (PCA) and Factor Analysis (FA) with geochemical data: problems and possibilities. Seminar or the Norwegian Geological Survey, Trondheim, Non-EU.
| Principal Component Analysis (PCA) and Factor Analysis (FA) with geochemical data: problems and possibilities at reposiTUm , opens an external URL in a new window
Reimann, C., Filzmoser, P., Garrett, R. G., & Dutter, R. (2008). Statistical Data Analysis Explained. Applied Environmental Statistics with R. John Wiley & Sons.
| Statistical Data Analysis Explained. Applied Environmental Statistics with R. at reposiTUm , opens an external URL in a new window
Templ, M., & Filzmoser, P. (2008). Visualization and the use of R-Forge for collaborative research projects. AMELI kick-off meeting, Neuchatel, Non-EU.
| Visualization and the use of R-Forge for collaborative research projects at reposiTUm , opens an external URL in a new window
Templ, M., & Filzmoser, P. (2008). Visualization of missing values using the R-package VIM (CS-2008-1).
| Visualization of missing values using the R-package VIM at reposiTUm , opens an external URL in a new window
Templ, M., Alfons, A., & Filzmoser, P. (2008). Recent Developments in Visualization : Focus on Missing Values and Maps. AMELI Meeting, Wiesbaden, EU.
| Recent Developments in Visualization : Focus on Missing Values and Maps at reposiTUm , opens an external URL in a new window
Templ, M., Filzmoser, P., & Reimann, C. (2008). Cluster Analysis: Data preparation? Which algorithm? How many clusters? Lifestat 2008, München, EU.
| Cluster Analysis: Data preparation? Which algorithm? How many clusters? at reposiTUm , opens an external URL in a new window
Templ, M., Filzmoser, P., & Reimann, C. (2008). Cluster analysis applied to regional geochemical data: Problems and possibilities. Applied Geochemistry, 23(8), 2198–2213.
| Cluster analysis applied to regional geochemical data: Problems and possibilities at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2008). An Object Oriented Framework for Robust Multivariate Analysis in R. In Abstracts of the International Conference On Robust Statistics (p. 100).
| An Object Oriented Framework for Robust Multivariate Analysis in R at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2008). Robuste multivariate Analyse in R. In Abstracts of the Workshop TU Wien/TU Dresden (p. 27).
| Robuste multivariate Analyse in R at reposiTUm , opens an external URL in a new window
Varmuza, K., & Filzmoser, P. (2008). Comparison of some Linear Regression Methods - Available in R - for a QSPR Problem. In 22. CIC- Workshop (p. 96).
| Comparison of some Linear Regression Methods - Available in R - for a QSPR Problem at reposiTUm , opens an external URL in a new window
Weisser, A., Endel, G., Filzmoser, P., & Gyimesi, M. (2008). ATC-#gtICD - evaluating the reliability of prognoses for ICD-10 diagnoses derived from the ATC-Code of prescriptions. BMC Health Services Research, 8, 10.
| ATC-#gtICD - evaluating the reliability of prognoses for ICD-10 diagnoses derived from the ATC-Code of prescriptions at reposiTUm , opens an external URL in a new window
Wieser, R., & Filzmoser, P. (2008). Anwendung statistischer Verfahren auf einen kommunalen Datensatz (CS-2008-7).
| Anwendung statistischer Verfahren auf einen kommunalen Datensatz at reposiTUm , opens an external URL in a new window
Wieser, R., Filzmoser, P., Baaske, W. E., & Mader, W. (2008). An Application of Robust Variable Selection with many Variables. In Abstracts of the International Conference On Robust Statistics (p. 115).
| An Application of Robust Variable Selection with many Variables at reposiTUm , opens an external URL in a new window
Wieser, R., Filzmoser, P., Baaske, W. E., & Mader, W. (2008). Anwendung robuster Variablenselektionsverfahren zur Analyse hochdimensionaler Daten. In Abstracts of the Workshop TU Wien/TU Dresden (p. 32).
| Anwendung robuster Variablenselektionsverfahren zur Analyse hochdimensionaler Daten at reposiTUm , opens an external URL in a new window

Croux, C., & Filzmoser, P. (2007). A survey of robust statistics. Statistical Methods & Applications, 15, 280–282.
| A survey of robust statistics at reposiTUm , opens an external URL in a new window
Croux, C., Filzmoser, P., & Oliveira, M. R. (2007). Algorithms for Projection-Pursuit robust principal component analysis. Chemometrics and Intelligent Laboratory Systems, 87, 218–225.
| Algorithms for Projection-Pursuit robust principal component analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2007). Data Quality Issues for Statistical Methods. 11th Meeting of CEN/TG 230/WG 2, Wien, Austria.
| Data Quality Issues for Statistical Methods at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2007). Package mvoutlier for Multivariate Outlier Detection. International Workshop on Robust Statistics and R, Treviso, Italy, Austria.
| Package mvoutlier for Multivariate Outlier Detection at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2007). Robust PCA for Flat Data. International Workshop on Computational and Financial Econometrics, Genf, Non-EU.
| Robust PCA for Flat Data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2007). Robust Principal Components. Jubilee International Conference 60 years Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia, EU.
| Robust Principal Components at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2007). Robuste Schätzung am Beispiel von Hauptkomponentenanalyse. Seminar of the Department of Mathematical Stochastics, Dresden, EU.
| Robuste Schätzung am Beispiel von Hauptkomponentenanalyse at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2007). Robustness for Compositional Data. Seminar für Statistik, Dortmund, EU.
| Robustness for Compositional Data at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2007). Robustness for Large Data Sets: New Challenges in High Dimension. Seminar of the Department of Statistics, Univ. Toulouse I, Toulouse, EU.
| Robustness for Large Data Sets: New Challenges in High Dimension at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Fritz, H. (2007). Exploring high-dimensional data with robust principal components (CS-2007-2).
| Exploring high-dimensional data with robust principal components at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Fritz, H. (2007). Exploring High-dimensional Data with Robust Principal Components. In Proceedings of the Eighth International Conference Computer Data Analysis and Modeling (pp. 43–50). Publishing center BSU, Minsk.
| Exploring High-dimensional Data with Robust Principal Components at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Hron, K. (2007). Outlier detection for compositional data using robust methods (CS-2007-1).
| Outlier detection for compositional data using robust methods at reposiTUm , opens an external URL in a new window
Filzmoser, P., Hron, K., & Reimann, C. (2007). Principal component analysis for compositional data with outliers (SM-2007-3).
| Principal component analysis for compositional data with outliers at reposiTUm , opens an external URL in a new window
Filzmoser, P., Reimann, C., Ruiz-Gazen, A., & Thomas-Agnan, C. (2007). Exploratory Tools for Spatial Multivariate Outlier Detection. International Conference on Robust Statistics (ICORS 2007), Buenos Aires, Non-EU.
| Exploratory Tools for Spatial Multivariate Outlier Detection at reposiTUm , opens an external URL in a new window
Filzmoser, P., Serneels, S., Maronna, R., & Van Espen, P. J. (2007). Robust multivariate methods in chemometrics (CS-2007-3).
| Robust multivariate methods in chemometrics at reposiTUm , opens an external URL in a new window
Fritz, H., Filzmoser, P., & Templ, M. (2007). Robust Estimation of Missing Values. International Workshop on Robust Statistics and R, Treviso, Italy, Austria.
| Robust Estimation of Missing Values at reposiTUm , opens an external URL in a new window
Hron, K., & Filzmoser, P. (2007). Outlier Detection for Compositional Data and Applications to Environmetrics. TIES 2007, 18th annual meeting of the International Environmetrics Society, Mikulov, EU.
| Outlier Detection for Compositional Data and Applications to Environmetrics at reposiTUm , opens an external URL in a new window
Liebminger, A., Seyfang, L., Filzmoser, P., & Varmuza, K. (2007). A new variable selection method based on all subsets regression. In Book of Abstracts. 10#^{th} Scandinavian Symposium on Chemometrics, Lappeenranta, Finnland, EU.
| A new variable selection method based on all subsets regression at reposiTUm , opens an external URL in a new window
Neykov, N., Filzmoser, P., Dimova, R., & Neytchev, P. (2007). Robust fitting of mixtures using the trimmed likelihood estimator. Computational Statistics & Data Analysis, 52, 299–308.
| Robust fitting of mixtures using the trimmed likelihood estimator at reposiTUm , opens an external URL in a new window
Reimann, C., Arnoldussen, A., Englmaier, P., Filzmoser, P., Finne, T. E., Garrett, R. G., Koller, F., & Nordgulen, O. (2007). Element concentrations and variations along a 120-km transect in southern Norway - Anthropogenic vs. geogenic vs. biogenic element sources and cycles. Applied Geochemistry, 22, 851–871.
| Element concentrations and variations along a 120-km transect in southern Norway - Anthropogenic vs. geogenic vs. biogenic element sources and cycles at reposiTUm , opens an external URL in a new window
Ruiz-Gazen, A., Thomas-Agnan, C., Filzmoser, P., & Reimann, R. (2007). Exploratory Tools for Spatial Multivariate Outlier Detection. 6th Spatial Econometrics and Statistics Workshop, Dijon, EU.
| Exploratory Tools for Spatial Multivariate Outlier Detection at reposiTUm , opens an external URL in a new window
Seyfang, L., Filzmoser, P., & Varmuza, K. (2007). Variable selection by all subsets regression and by genetic algorithms. In Proc.of Conferentia Chemometrica. Conferentia Chemometrica 2007, Budapest, EU.
| Variable selection by all subsets regression and by genetic algorithms at reposiTUm , opens an external URL in a new window
Templ, M., & Filzmoser, P. (2007). Visualisation of Missing Values and Robust Imputation in Environmental Surveys. TIES 2007, 18th annual meeting of the International Environmetrics Society, Mikulov, EU.
| Visualisation of Missing Values and Robust Imputation in Environmental Surveys at reposiTUm , opens an external URL in a new window
Templ, M., Filzmoser, P., & Reimann, C. (2007). Problems and Possibilities of Cluster Analysis: Application on Geochemical Data. ROeS Seminar 2007, Bern, Non-EU.
| Problems and Possibilities of Cluster Analysis: Application on Geochemical Data at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2007). Robust Statistic for the One-way MANOVA. TIES 2007, 18th annual meeting of the International Environmetrics Society, Mikulov, EU.
| Robust Statistic for the One-way MANOVA at reposiTUm , opens an external URL in a new window
Todorov, V., & Filzmoser, P. (2007). Robust statistic for the one-way MANOVA (CS-2007-7).
| Robust statistic for the one-way MANOVA at reposiTUm , opens an external URL in a new window

Fazekas, I., & Filzmoser, P. (2006). A Functional Central Limit Theorem for Kernel Type Density Estimators. Austrian Journal of Statistics, 35(4), 409–418.
| A Functional Central Limit Theorem for Kernel Type Density Estimators at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2006). Analysing Multivariate Data: Methods and their Piftalls. Arsenal Research, Wien, Austria.
| Analysing Multivariate Data: Methods and their Piftalls at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2006). Extremwerte oder Ausreißer. Seminar of Department of Applied Statistics, Leuven, EU.
| Extremwerte oder Ausreißer at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2006). Outlier Detection in Very High Dimension. University of Liege, Belgien, EU.
| Outlier Detection in Very High Dimension at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2006). Outlier Detection with Application to Geochemistry. The R User Conference 2006, Wien, EU.
| Outlier Detection with Application to Geochemistry at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2006). Outlier Identification in High Dimensions. International Conference on Robust Statistics (ICORS 2006), Lissabon, EU.
| Outlier Identification in High Dimensions at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2006). Outliers or Extremes. Seminar of Department of Applied Statistics, Leuven, EU.
| Outliers or Extremes at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2006). Projection Pursuit Algorithms for Robust Multivariate Methods. Robust Classification and Discrimination with High Dimensional Data, Florenz, EU.
| Projection Pursuit Algorithms for Robust Multivariate Methods at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2006). What can Robust Statistics Offer for Practice? Geological Survey of Norway, Trondheim, Non-EU.
| What can Robust Statistics Offer for Practice? at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Filzmoser, H. (2006). Ermittlung der Wahrscheinlichkeit einer Nichteinhaltung des Sicherheitsabstandes zwischen Ankerbohrungen, C-2006-4.
| Ermittlung der Wahrscheinlichkeit einer Nichteinhaltung des Sicherheitsabstandes zwischen Ankerbohrungen, C-2006-4 at reposiTUm , opens an external URL in a new window
Filzmoser, P., Joossens, K., & Croux, C. (2006). Multiple group discriminant analysis: Robustness and error rate, CS-2006-1.
| Multiple group discriminant analysis: Robustness and error rate, CS-2006-1 at reposiTUm , opens an external URL in a new window
Filzmoser, P., Joossens, K., & Croux, C. (2006). Multiple group linear discriminant analysis: robustness and error rate. In A. Rizzi & M. Vichi (Eds.), Compstat 2006, Proceedings in Computational Statistics (pp. 521–532).
| Multiple group linear discriminant analysis: robustness and error rate at reposiTUm , opens an external URL in a new window
Filzmoser, P., Maronna, R., Dimova, R., & Werner, M. (2006). Outlier identification in high dimensions, CS-2006-3.
| Outlier identification in high dimensions, CS-2006-3 at reposiTUm , opens an external URL in a new window
Filzmoser, P., Serneels, S., Croux, C., & Van Espen, P. J. (2006). Robust Multivariate Methods: The Projection Pursuit Approach. In M. Spiliopoulou, R. Kruse, C. Borgelt, A. Nürnberger, & W. Gaul (Eds.), From Data and Information Analysis to Knowledge Engineering (pp. 270–277).
| Robust Multivariate Methods: The Projection Pursuit Approach at reposiTUm , opens an external URL in a new window
Janauer, G., Filzmoser, P., Otahelova, H., Gaberscik, A., Topic, J., Berczik, A., Igic, R., Vulchev, V., Sarbu, A., Kohler, A., & Exler, N. (2006). Macrophyte Habitat Preference, River Restoration, and the WFD: making use of the MIDCC data base. In Proceedings 36th International Conference of IAD (pp. 81–85). Austrian Committee Danube Research/IAD.
| Macrophyte Habitat Preference, River Restoration, and the WFD: making use of the MIDCC data base at reposiTUm , opens an external URL in a new window
Janauer, G., Lanz, E., Filzmoser, P., & Exler, N. (2006). Breg and Brigach, source streams of the Danube: changes based on macrophyte surveys 1967, 1989, and 2004. In Proceedings 36th International Conference of IAD (pp. 86–90). Austrian Committee Danube Research/IAD.
| Breg and Brigach, source streams of the Danube: changes based on macrophyte surveys 1967, 1989, and 2004 at reposiTUm , opens an external URL in a new window
Neykov, N., Filzmoser, P., Dimova, R., & Neytchev, P. (2006). Robust fitting of mixtures using the Trimmed Likelihood Estimator, CS-2006-2.
| Robust fitting of mixtures using the Trimmed Likelihood Estimator, CS-2006-2 at reposiTUm , opens an external URL in a new window
Richter, B., Gwechenberger, M., Filzmoser, P., Marx, M., Lercher, P., & Gössinger, H. D. (2006). Is inducibility of atrial fibrillation after radio frequency ablation really a relevant prognostic factor? European Heart Journal, 27, 2553–2559.
| Is inducibility of atrial fibrillation after radio frequency ablation really a relevant prognostic factor? at reposiTUm , opens an external URL in a new window
Sarbu, A., Janauer, G., Exler, N., & Filzmoser, P. (2006). The aquatic vegetation of large Danube river branches in Romania. In Proceedings 36th International Conference of IAD (pp. 101–106). Austrian Committee Danube Research/IAD.
| The aquatic vegetation of large Danube river branches in Romania at reposiTUm , opens an external URL in a new window
Serneels, S., Croux, C., Filzmoser, P., & Van Espen, P. J. (2006). The Partial Robust M-approach. In M. Spiliopoulou, R. Kruse, C. Borgelt, A. Nürnberger, & W. Gaul (Eds.), From Data and Information Analysis to Knowledge Engineering (pp. 230–237). Springer.
| The Partial Robust M-approach at reposiTUm , opens an external URL in a new window
Templ, M., & Filzmoser, P. (2006). Stability of Cluster Analysis. The R User Conference 2006, Wien, EU.
| Stability of Cluster Analysis at reposiTUm , opens an external URL in a new window
Templ, M., Filzmoser, P., & Reimann, R. (2006). Cluster Analysis applied to regional geochemical data: Problems and possibilities, CS-2006-5.
| Cluster Analysis applied to regional geochemical data: Problems and possibilities, CS-2006-5 at reposiTUm , opens an external URL in a new window
Zick, D., Gassner, H., Filzmoser, P., Wanzenböck, J., Pamminger-Lahnsteiner, B., & Tischler, G. (2006). Changes in the fish species composition of all Austrian lakes #gt50 ha during the last 150 years. Fisheries Management and Ecology, 13, 103–111.
| Changes in the fish species composition of all Austrian lakes #gt50 ha during the last 150 years at reposiTUm , opens an external URL in a new window

Branco, J., Croux, C., Filzmoser, P., & Oliveira, M. R. (2005). Robust Canonical Correlations: A Comparative Study. Computational Statistics, 20, 203–229.
| Robust Canonical Correlations: A Comparative Study at reposiTUm , opens an external URL in a new window
Croux, C., Filzmoser, P., & Joossens, K. (2005). Robust linear discriminant analysis for multiple groups: influence and classification efficiencies, CS-2005-1.
| Robust linear discriminant analysis for multiple groups: influence and classification efficiencies, CS-2005-1 at reposiTUm , opens an external URL in a new window
Dutter, R., Filzmoser, P., & Kharin, Y. (Eds.). (2005). Austrian Journal of Statistics. Österreichische Statistische Gesellschaft.
| Austrian Journal of Statistics at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2005). Analyzing Data with Robust Statistical Methods. VRVis Center, Vienna, Austria.
| Analyzing Data with Robust Statistical Methods at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2005). Multivariate Outlier Detection with Application to Geochemistry. Seminar of the Department of Statistics, Univ. Toulouse, Toulouse, Austria.
| Multivariate Outlier Detection with Application to Geochemistry at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2005). Multivariate und robuste Statistik in der Praxis. Forum Junge Statistik, Austrian Statistical Society, Vienna, Austria.
| Multivariate und robuste Statistik in der Praxis at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2005). Partial Robust M-Regression. International Conference on Robust Statistics, Parma, EU.
| Partial Robust M-Regression at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2005). Partial Robust Regression versus Robust Partial Least Squares. Perspectives in Modern Statistical Inference III, Mikulov, Czech Republic, Austria.
| Partial Robust Regression versus Robust Partial Least Squares at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2005). Robuste Statistik zur Erkennung multivariater Ausreißer. Wissenwertes aus der Mathematik, Wien, Austria.
| Robuste Statistik zur Erkennung multivariater Ausreißer at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2005). Statistical Analysis of Data from the MIDCC Project, Advanced Statistical Analysis. Workshop MIDCC, Mosonmagyarovar, Austria.
| Statistical Analysis of Data from the MIDCC Project, Advanced Statistical Analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2005). The Package pcaPP: PCA by Projection Pursuit. International Workshop on Robust Statistics and R, Treviso, Italy, Austria.
| The Package pcaPP: PCA by Projection Pursuit at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2005). The Projection Pursuit Approach for Robust Multivariate Analysis. ISDS Kolloquium, University of Vienna, Austria.
| The Projection Pursuit Approach for Robust Multivariate Analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2005). Identification of Multivariate Outliers: A Performance Study. Austrian Journal of Statistics, 34, 2, 127–138.
| Identification of Multivariate Outliers: A Performance Study at reposiTUm , opens an external URL in a new window
Filzmoser, P., Garrett, R. G., & Reimann, C. (2005). Multivariate outlier detection in exploration geochemistry. COMPUTERS & GEOSCIENCES, 31, 579–587.
| Multivariate outlier detection in exploration geochemistry at reposiTUm , opens an external URL in a new window
Reimann, C., Filzmoser, P., & Garrett, R. G. (2005). Background and threshold: critical comparison of methods of determination. Science of the Total Environment, 346, 1–16.
| Background and threshold: critical comparison of methods of determination at reposiTUm , opens an external URL in a new window
Serneels, S., Croux, C., Filzmoser, P., & Van Espen, P. J. (2005). Partial robust M-regression. Chemometrics and Intelligent Laboratory Systems, 79, 55–64.
| Partial robust M-regression at reposiTUm , opens an external URL in a new window
Serneels, S., Croux, C., Filzmoser, P., & Van Espen, P. J. (2005). Robust continuum regression. Chemometrics and Intelligent Laboratory Systems, 76(2), 197–204.
| Robust continuum regression at reposiTUm , opens an external URL in a new window
van Helvoort, P.-J., Filzmoser, P., & van Gaans, P. F. M. (2005). Sequential Factor Analysis as a new approach to multivariate analysis of heterogeneous geochemical datasets: An application to a bulk chemical characterization of fluvial deposits (Rhine-Meuse delta, The Netherlands. Applied Geochemistry, 20, 2233–2251.
| Sequential Factor Analysis as a new approach to multivariate analysis of heterogeneous geochemical datasets: An application to a bulk chemical characterization of fluvial deposits (Rhine-Meuse delta, The Netherlands at reposiTUm , opens an external URL in a new window

Aivazian, S., Filzmoser, P., & Kharin, Y. (Eds.). (2004). Computer Data Analysis and Modeling: Robustness and Computer Intensive Methods. Proceedings of the Seventh International Conference, Volume 1. Belarusian State University.
| Computer Data Analysis and Modeling: Robustness and Computer Intensive Methods. Proceedings of the Seventh International Conference, Volume 1 at reposiTUm , opens an external URL in a new window
Croux, C., Filzmoser, P., & Oliveira, M. R. (2004). Projection-pursuit Estimators for Robust Principal Component Analysis, TS-04-4.
| Projection-pursuit Estimators for Robust Principal Component Analysis, TS-04-4 at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2004). A Multivariate Outlier Detection Method. Konferenz CDAM (Computer Data Analysis and Modeling), Minsk, Austria.
| A Multivariate Outlier Detection Method at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2004). An Adaptive Method for Multivariate Outlier Detection. International Conference on Robust Statistics, Parma, EU.
| An Adaptive Method for Multivariate Outlier Detection at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2004). Identification of Multivariate Outliers: A Performance Study, TS-04-3.
| Identification of Multivariate Outliers: A Performance Study, TS-04-3 at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2004). Konzepte der robusten Statistik mit Anwendungen. Seminarreihe von VRVis Center, Wien, Austria.
| Konzepte der robusten Statistik mit Anwendungen at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2004). Partial Least Squares Regression. Workshop “Robust Analysis of Large Data Sets,” Banff, Kanada, Austria.
| Partial Least Squares Regression at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2004). Statistical Analysis of Data from the MIDCC Project. Workshop MIDCC, Mosonmagyarovar, Austria.
| Statistical Analysis of Data from the MIDCC Project at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2004). Statistical Methods in Developing Quality Assessment Criteria. Workshop "What’s fishy about the Water Framework Directive?, Stockholm, Austria.
| Statistical Methods in Developing Quality Assessment Criteria at reposiTUm , opens an external URL in a new window
Neykov, N., Filzmoser, P., Dimova, R., & Neytchev, P. (2004). Mixture of GLMs and the trimmed likelihood methodology. Compstat 2004, Prag, Austria.
| Mixture of GLMs and the trimmed likelihood methodology at reposiTUm , opens an external URL in a new window
Serneels, S., Croux, C., Filzmoser, P., & Van Espen, P. J. (2004). Robust Partial M-Regression, TS-04-2.
| Robust Partial M-Regression, TS-04-2 at reposiTUm , opens an external URL in a new window
van Helvoort, P. J., Filzmoser, P., & van Gaans, P. F. M. (2004). Sequential factor analysis as a new approach to multivariate analysis of heterogeneous geochemical datasets: an application to a bulk chemical characterization of fluvial deposits (Rhine-Meuse delta, the Netherlands), TS-04-1.
| Sequential factor analysis as a new approach to multivariate analysis of heterogeneous geochemical datasets: an application to a bulk chemical characterization of fluvial deposits (Rhine-Meuse delta, the Netherlands), TS-04-1 at reposiTUm , opens an external URL in a new window

Branco, J., Croux, C., Filzmoser, P., & Oliveira, M. R. (2003). Robust canonical correlations: a comparative study, TS-03-4.
| Robust canonical correlations: a comparative study, TS-03-4 at reposiTUm , opens an external URL in a new window
Croux, C., & Filzmoser, P. (2003). Projection pursuit based mesasures of association, TS-03-3.
| Projection pursuit based mesasures of association, TS-03-3 at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2003). A statistical method for finding indicators of water quality. Symposium on "How to assess and monitor ecological quality in freshwaters, Helsinki, Austria.
| A statistical method for finding indicators of water quality at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2003). Maße für Assoziation basierend auf Projection Pursuit. Österreichische Statistiktage 2003, Wien, Austria.
| Maße für Assoziation basierend auf Projection Pursuit at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2003). Measures of Association based on Projection Pursuit. International Conference on Robust Statistics (ICORS 2003), Antwerpen, Austria.
| Measures of Association based on Projection Pursuit at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2003). Multivariate Outlier Detection and Visualization. StatGIS 2003: Interfacing Geostatistics, GIS and Spatial Databases, Pörtschach, Kärnten, Austria.
| Multivariate Outlier Detection and Visualization at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2003). Robust factor analysis and extended models. Institut für Angewandte Mathematik, Masaryk Universität, Brno, Brno, Austria.
| Robust factor analysis and extended models at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2003). Robuste Faktorenanalyse und erweiterte Modelle. Institut f. Ökonometrie, Operations Research und Systemtheorie, TU wien, Austria.
| Robuste Faktorenanalyse und erweiterte Modelle at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2003). Univariate and Multivariate Outlier Detection with Application to Geochemical Data. RMED’03: Workshop on Robust Modeling of Environmental Data, Vorau, Austria.
| Univariate and Multivariate Outlier Detection with Application to Geochemical Data at reposiTUm , opens an external URL in a new window
Filzmoser, P., Garrett, R. G., & Reimann, C. (2003). Multivariate outlier detection in exploration geochemistry, TS-03-5.
| Multivariate outlier detection in exploration geochemistry, TS-03-5 at reposiTUm , opens an external URL in a new window
Janauer, G., & Filzmoser, P. (2003). Statistical consideration for monitoring macrophytes in lakes according to the water framework directive: Towards minimising the survey effort, TS-03-6.
| Statistical consideration for monitoring macrophytes in lakes according to the water framework directive: Towards minimising the survey effort, TS-03-6 at reposiTUm , opens an external URL in a new window
Oliveira, M. R., Branco, J., Croux, C., & Filzmoser, P. (2003). Robust Redundancy analysis by alternating regression, TS-03-2.
| Robust Redundancy analysis by alternating regression, TS-03-2 at reposiTUm , opens an external URL in a new window
Reimann, C., Filzmoser, P., & Garrett, R. G. (2003). Background and threshold - the need for visualisation, TS-03-1.
| Background and threshold - the need for visualisation, TS-03-1 at reposiTUm , opens an external URL in a new window

Christodoulides, P., & Filzmoser, P. (2002). Hauptebenenanalyse - eine Erweiterung der Hauptkomponentenanalyse. Österreichische Statistiktage 2002, Wien, Austria.
| Hauptebenenanalyse - eine Erweiterung der Hauptkomponentenanalyse at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2002). Dimension reduction of the explanatory variables in (robust) multiple linear regression. XXII International Seminar on Stability Problems for Stochastic Models and Seminar on Statistical Data Analysis (SDA 2002), Varna, Austria.
| Dimension reduction of the explanatory variables in (robust) multiple linear regression at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2002). Robust estimation of the parameters in the FANOVA model. Instituto Superior Tecnico Lisbon, Lissabon, Austria.
| Robust estimation of the parameters in the FANOVA model at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2002). Robust factor analysis. International Conference on Robust Statistics, Parma, EU.
| Robust factor analysis at reposiTUm , opens an external URL in a new window
Filzmoser, P. (2002). Robust fitting of additive and multiplicative models. Universite Libre de Bruxelles, Bruxelles, Austria.
| Robust fitting of additive and multiplicative models at reposiTUm , opens an external URL in a new window
Filzmoser, P., & Viertl, R. (2002). Testing hypotheses with fuzzy data: The fuzzy p-value, RIS-2002-3.
| Testing hypotheses with fuzzy data: The fuzzy p-value, RIS-2002-3 at reposiTUm , opens an external URL in a new window
Kavsek, B., & Filzmoser, P. (2002). PLS - Regression und ihre Anwendungen. Österreichische Statistiktage 2002, Wien, Austria.
| PLS - Regression und ihre Anwendungen at reposiTUm , opens an external URL in a new window

Name	Purpose	Lifetime	Type	Provider
CookieConsent	Saves your settings for the use of cookies on this website.	1 year	HTML	Homepage TU Wien
SimpleSAML	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	Login TU Wien
SimpleSAMLAuthToken	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	Login TU Wien
fe_typo_user	Is needed so that in case of a Typo3 frontend login the session ID is recognized to grant access to protected areas.	session	HTTP	Homepage TU Wien
staticfilecache	Is needed to optimize the delivery time of the website.	session	HTTP	Homepage TU Wien
JESSIONSID	Is needed so that in case of a LectureTube the session ID is recognized to grant access to protected areas.	session	HTTP	LectureTube TU Wien
_shibsession_lecturetube	This is needed to distinguish between the sessions of the logged-in users.	session	HTTP	LectureTube TU Wien

Name	Purpose	Lifetime	Type	Provider
_pk_id	Used to store a few details about the user such as the unique visitor ID.	13 months	HTML	Matomo TU Wien
_pk_ref	Is used to store the information of the users home website.	6 months	HTML	Matomo TU Wien
_pk_ses	Is needed to store temporary data of the visit.	30 minutes	HTML	Matomo TU Wien
nmstat	Is used to record the behaviour on the website. It is used to collect statistics about website usage, such as when the visitor last visited the website. The cookie does not contain any personal data and is only used for website analysis.	1000 days	HTML	Siteimprove
siteimproveses	Is used to track the sequence of pages that a visitor views during his/her visit to the website. The cookie does not contain any personal data and is used solely for website analysis.	session	HTTP	Siteimprove
AWSELB	Always occurs in pairs with siteimproveses (for load balancing on the provider server)	session	HTTP	Siteimprove

Name	Purpose	Lifetime	Type	Provider
_ga	Is needed to distinguish the sessions of the users from each other.	persistent	HTTP	Google Analytics
_gali	Is needed to determine which links are clicked on a page.	expires immediately	HTTP	Google Analytics
_gat	This is a function-related cookie, whose tasks may differ.	2 years	HTTP	Google Analytics
_gid	Is needed to distinguish users and create statistics.	24 hours	HTTP	Google Analytics
_gads	Required to enable websites to display advertising from Google, including personalized advertising.	13 months	HTTP	Google Analytics
_gac_	Required by advertisers to measure user activity and the performance of their advertising campaigns.	90 days	HTTP	Google Analytics
_gcl_	Required by advertisers to determine how often users who click on their ads end up taking an action on their website.	90 days	HTTP	Google Analytics
_gcl_au	Contains a randomly generated user ID.	90 days	HTTP	Google
_gcl_aw	Is set when users click on a Google ad on the website and contains information about which ad was clicked.	90 days	HTTP	Google
__utma	Is used to record visits and visitors.	2 years	HTTP	Google Analytics
__utmb	Is used to detect new visits.	30 minutes	HTTP	Google Analytics
__utmc	Is used in connection with __utmb to determine whether it is a new (recent) visit.	session	HTTP	Google Analytics
__utmd	Is used to store and track visitor journeys through the site and classifies them into groups (marketing/tracking).	1 second	HTTP	Google Analytics
__utmt	Is needed to limit the query rate on Google Analytics.	10 minutes	HTTP	Google Analytics
__utmz	Is needed to determine from which source/campaign visitors come.	6 months	HTTP	Google Analytics
__utmvc	Is needed to collect information about user behavior on multiple websites. This information is used to optimize the relevance of advertising on the website.	24 hours	HTTP	Google AdSense
utm_source	Is needed to tag URLs with parameters to identify the campaigns that forward traffic.	expires immediately	HTTP	Google Analytics
__utm.gif	Is needed to save browser details.	session	HTTP	Google Analytics
gtag	Is needed to perform remarketing.	30 days	HTTP	Google AdSense
id	Is needed to perform remarketing.	2 years	HTTP	Google AdWords
1P_JAR	Is needed to optimize advertising, provide ads that are relevant to users, improve campaign performance reports, or prevent users from seeing the same ads more than once.	2 years	HTTP	Google
AID	Is needed to activate targeted advertising.	2 years	HTTP	Google Analytics
ANID	Is needed to display Google ads on non-Google websites.	2 years	HTTP	Google AdSense
APISID	Unknown functionality	2 years	HTTP	Google Ads Optimization
AR	Is needed to profile visitors' interests and display relevant ads on other websites. This cookie works by uniquely identifying your browser and device.	2 years	HTTP	Google AdSense
CONSENT	Is needed to store the preferences of visitors and personalize advertising.	persistent	HTTP	Google
DSID	Is needed by DoubleClick for advertising displayed in various places on the web and used to store the preferences of users.	2 years	HTTP	Doubleclick
DV	Is needed to store user preferences and other information. This includes, in particular, the preferred language, the number of search results to be displayed on the page, and the decision whether or not to activate the Google SafeSearch filter.	2 years	HTTP	Google
HSID	Contains the Google account ID and the last login time of the user.	2 years	HTTP	Google
IDE	Is needed by DoubleClick to record and report the actions of users on the website after viewing or clicking on one of the provider's ads, with the purpose of measuring the effectiveness of an advertisement and displaying targeted advertisements to users.	2 years	HTTP	Doubleclick
LOGIN_INFO	Is used to store the credentials of users of Google services.	2 years	HTTP	Google
NID	Is used to store information about user settings.	6 months	HTTP	Google
OTZ	Is needed to link activities of visitors with other devices that are previously logged in via the Google account. In this way, advertising is tailored to different devices.	1 month	HTTP	Google
RUL	Is needed by DoubleClick to determine whether advertising has been displayed correctly in order to make marketing activities more efficient.	1 year	HTTP	Doubleclick
SAPISID	Is needed by YouTube to store user settings and to calculate user bandwidth.	persistent	HTTP	Google
SEARCH_SAMESITE	Enables servers to mitigate the risk of CSRF and information leakage attacks by specifying that a particular cookie may only be sent on requests originating from the same registerable domain.	6 months	HTTP	Google
SID	Contains the Google account ID and the last login time of the user.	2 years	HTTP	Google
SIDCC	Is needed to store information about user settings and information for Google Maps.	3 months	HTTP	Google
SSID	Is needed to collect visitor information for videos hosted by YouTube on Google Maps integrated maps.	persistent	HTTP	Google
__SECURE-1PAPISID	Is needed for targeting purposes to create a profile of the interests of website visitors.	2 years	HTTP	Google
__SECURE-1PSID	Is needed for targeting purposes to create a profile of the interests of website visitors.	2 years	HTTP	Google
__SECURE-3PAPISID	Is needed for targeting purposes to create a profile of the interests of website visitors.	2 years	HTTP	Google
__SECURE-3PSID	Is needed for targeting purposes to create a profile of the interests of website visitors.	2 years	HTTP	Google
__SECURE-3PSIDCC	Is needed for targeting purposes to create a profile of the interests of website visitors.	2 years	HTTP	Google
__SECURE-APISID	Is needed to profile the interests of website visitors in order to display relevant and personalized advertising through retargeting.	8 months	HTTP	Google
__SECURE-HSID	Is needed to secure digitally signed and encrypted data from the unique Google ID and to store the last login time that Google uses to identify visitors, prevent fraudulent use of login data, and protect visitor data from unauthorized parties. This may also be used for targeting purposes to display relevant and personalized advertising content.	8 months	HTTP	Google
__SECURE-SSID	Is needed to store information about how visitors use the site and about the ads they may have seen before visiting the site. Also used to customize ads on Google domains.	8 months	HTTP	Google
test_cookie	Is set as a test to check whether the browser allows cookies to be set. Does not contain any identification features.	15 minutes	HTTP	Google
VISITOR_INFO1_LIVE	Is needed by YouTube to store user settings and to calculate user bandwidth.	6 months	HTTP	Youtube
facebook	Is used to Enable ad delivery or retargeting	90 days	HTTP	Meta (Facebook)
__fb_chat_plugin	Is needed to store and track interactions (marketing/tracking).	persistent	HTTP	Meta (Facebook)
_js_datr	Is needed to save user settings.	2 years	HTTP	Meta (Facebook)
_fbc	Is needed to save the last visit (marketing/tracking).	2 years	HTTP	Meta (Facebook)
fbm	Is needed to store account data (marketing/tracking).	1 year	HTTP	Meta (Facebook)
xs	Is needed to store a unique session ID (marketing/tracking).	1 year	HTTP	Meta (Facebook)
wd	Is needed to log the screen resolution.	1 week	HTTP	Meta (Facebook)
fr	Is needed to serve ads and measure and improve their relevance.	3 months	HTTP	Meta (Facebook)
act	Is needed to store logged in users (marketing/tracking).	90 days	HTTP	Meta (Facebook)
_fbp	Is needed to store and track visits to various websites (marketing/tracking).	3 months	HTTP	Meta (Facebook)
datr	Is needed to identify the browser for security and website integrity purposes, including account recovery and identification of potentially compromised accounts.	2 years	HTTP	Meta (Facebook)
dpr	Is used for analysis purposes. Technical parameters are logged (e.g. aspect ratio and dimensions of the screen) so that Facebook apps can be displayed correctly.	1 week	HTTP	Meta (Facebook)
sb	Is needed to store browser details and security information of the Facebook account.	2 years	HTTP	Meta (Facebook)
dbln	Is needed to store browser details and security information of the Facebook account.	2 years	HTTP	Meta (Facebook)
spin	Is needed for promotional purposes and social campaign reporting.	session	HTTP	Meta (Facebook)
presence	Contains the "chat" status of logged in users.	1 month	HTTP	Meta (Facebook)
cppo	Is needed for statistical purposes.	90 days	HTTP	Meta (Facebook)
locale	Is needed to save the language settings.	session	HTTP	Meta (Facebook)
pl	Required for Facebook Pixel.	2 years	HTTP	Meta (Facebook)
lu	Required for Facebook Pixel.	2 years	HTTP	Meta (Facebook)
c_user	Required for Facebook Pixel.	3 months	HTTP	Meta (Facebook)
bcookie	Is needed to store browser data (marketing/tracking).	2 years	HTTP	LinkedIn
li_oatml	Is needed to identify LinkedIn members outside of LinkedIn for advertising and analytics purposes.	1 month	HTTP	LinkedIn
BizographicsOptOut	Is needed to save privacy settings.	10 years	HTTP	LinkedIn
li_sugr	Is needed to store browser data (marketing/tracking).	3 months	HTTP	LinkedIn
UserMatchHistory	Is needed to provide advertising or retargeting (marketing/tracking).	30 days	HTTP	LinkedIn
linkedin_oauth_	Is needed to provide cross-page functionality.	session	HTTP	LinkedIn
lidc	Is needed to store performed actions on the website (marketing/tracking).	1 day	HTTP	LinkedIn
bscookie	Is needed to store performed actions on the website (marketing/tracking).	2 years	HTTP	LinkedIn
X-LI-IDC	Is needed to provide cross-page functionality (marketing/tracking).	session	HTTP	LinkedIn
AnalyticsSyncHistory	Stores the time when the user was synchronized with the "lms_analytics" cookie.	30 days	HTTP	LinkedIn
lms_ads	Is needed to identify LinkedIn members outside of LinkedIn.	30 days	HTTP	LinkedIn
lms_analytics	Is needed to identify LinkedIn members for analytics purposes.	30 days	HTTP	LinkedIn
li_fat_id	Required for indirect member identification used for conversion tracking, retargeting and analytics.	30 days	HTTP	LinkedIn
U	Is needed to identify the browser.	3 months	HTTP	LinkedIn
_guid	Is needed to identify a LinkedIn member for advertising via Google Ads.	90 days	HTTP	LinkedIn

Peter Filzmoser

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