Peter Filzmoser
Peter Filzmoser
Professor of Statistics, TU Wien
Verified email at - Homepage
Cited by
Cited by
Introduction to multivariate statistical analysis in chemometrics
K Varmuza, P Filzmoser
CRC press, 2016
Statistical data analysis explained: applied environmental statistics with R
C Reimann, P Filzmoser, R Garrett, R Dutter
John Wiley & Sons, 2011
Background and threshold: critical comparison of methods of determination
C Reimann, P Filzmoser, RG Garrett
Science of the total environment 346 (1-3), 1-16, 2005
Normal and lognormal data distribution in geochemistry: death of a myth. Consequences for the statistical treatment of geochemical and environmental data
C Reimann, P Filzmoser
Environmental geology 39 (9), 1001-1014, 2000
Repeated double cross validation
P Filzmoser, B Liebmann, K Varmuza
Journal of Chemometrics: A Journal of the Chemometrics Society 23 (4), 160-171, 2009
Factor analysis applied to regional geochemical data: problems and possibilities
C Reimann, P Filzmoser, RG Garrett
Applied geochemistry 17 (3), 185-206, 2002
Multivariate outlier detection in exploration geochemistry
P Filzmoser, RG Garrett, C Reimann
Computers & geosciences 31 (5), 579-587, 2005
Outlier identification in high dimensions
P Filzmoser, R Maronna, M Werner
Computational statistics & data analysis 52 (3), 1694-1711, 2008
Principal component analysis for compositional data with outliers
P Filzmoser, K Hron, C Reimann
Environmetrics: The Official Journal of the International Environmetrics …, 2009
Cluster analysis applied to regional geochemical data: problems and possibilities
M Templ, P Filzmoser, C Reimann
Applied Geochemistry 23 (8), 2198-2213, 2008
Univariate statistical analysis of environmental (compositional) data: problems and possibilities
P Filzmoser, K Hron, C Reimann
Science of the Total Environment 407 (23), 6100-6108, 2009
An object-oriented framework for robust multivariate analysis
V Todorov, P Filzmoser
Journal of Statistical Software 32, 1-47, 2010
robCompositions: an R-package for robust statistical analysis of compositional data
M Templ, K Hron, P Filzmoser
na 36, 341-354, 2011
Imputation of missing values for compositional data using classical and robust methods
K Hron, M Templ, P Filzmoser
Computational Statistics & Data Analysis 54 (12), 3095-3107, 2010
Algorithms for projection–pursuit robust principal component analysis
C Croux, P Filzmoser, MR Oliveira
Chemometrics and Intelligent Laboratory Systems 87 (2), 218-225, 2007
Exploratory factor analysis revisited: How robust methods support the detection of hidden multivariate data structures in IS research
H Treiblmaier, P Filzmoser
Information & management 47 (4), 197-207, 2010
Applied compositional data analysis
P Filzmoser, K Hron, M Templ
Cham: Springer, 2018
Outlier detection for compositional data using robust methods
P Filzmoser, K Hron
Mathematical Geosciences 40 (3), 233-248, 2008
Robust factor analysis
G Pison, PJ Rousseeuw, P Filzmoser, C Croux
Journal of multivariate analysis 84 (1), 145-172, 2003
Chemistry of Europe's Agricultural Soils: Methodology and Interpretation of the GEMAS Data Set
C Reimann, M Birke, A Demetriades, P Filzmoser, P O'Connor
Bundesanstalt für Geowissenschaftem und Rohstoffe, 2014
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