title: Review of robust multivariate statistical methods in high dimension.
abstract: General ideas of robust statistics, and specifically robust statistical methods for calibration and dimension reduction are discussed. The emphasis is on analyzing high-dimensional data. The discussed methods are applied using the packages chemometrics and rrcov of the statistical software environment R. It is demonstrated how the functions can be applied to real high-dimensional data from chemometrics, and how the results can be interpreted.
authors.affiliation: Department of Statistics and Probability Theory, Vienna University of Technology, Wiedner Hauptstr. 8-10, 1040 Vienna, Austria. p.filzmoser@tuwien.ac.at
authors.forename: Peter
authors.initials: P
authors.lastname: Filzmoser
authors.forename: Valentin
authors.initials: V
authors.lastname: Todorov