Title: Robust classification in high dimensions based on the SIMCA method
Authors: Vanden Branden, K ×
Hubert, Mia #
Issue Date: 2005
Publisher: Elsevier science bv
Series Title: Chemometrics and intelligent laboratory systems vol:79 issue:1-2 pages:10-21
Abstract: In this paper we first investigate the robustness of the SIMCA method for classifying high-dimensional observations. It turns out that both stages of the algorithm, the estimation of principal components and the construction of a classification rule, can be highly disturbed by the presence of outliers. Therefore we propose a robust procedure RSIMCA which is based on a robust Principal Component Analysis method for high-dimensional data (ROBPCA). Various simulations and real examples reveal the robustness of our approach. (c) 2005 Elsevier B.V. All rights reserved.
ISSN: 0169-7439
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Statistics Section
× corresponding author
# (joint) last author

Files in This Item:

There are no files associated with this item.

Request a copy


All items in Lirias are protected by copyright, with all rights reserved.

© Web of science