ITEM METADATA RECORD
Title: Principal component regression for data containing outliers and missing elements
Authors: Serneels, Sven ×
Verdonck, Tim #
Issue Date: Sep-2009
Publisher: North-Holland Pub. Co.
Series Title: Computational Statistics & Data Analysis vol:53 issue:11 pages:3855-3863
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. (C) 2009 Elsevier B.V. All rights reserved.
URI: 
ISSN: 0167-9473
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Non-KU Leuven Association publications
× 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