Title
Principal component regression for data containing outliers and missing elements Principal component regression for data containing outliers and missing elements
Author
Faculty/Department
Faculty of Sciences. Chemistry
Publication type
article
Publication
Amsterdam ,
Subject
Computer. Automation
Source (journal)
Computational statistics and data analysis. - Amsterdam
Volume/pages
53(2009) :11 , p. 3855-3863
ISSN
0167-9473
ISI
000267505600012
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
A methodology is presented to construct an expectation robust algorithm for principal component regression. The presented method is the first multivariate regression method which can resist outliers and which can cope with missing elements in the data simultaneously. Simulations and an example illustrate the good statistical properties of the method.
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