Principal component regression for data containing outliers and missing elements

Sven Serneels and Tim Verdonck

Computational Statistics & Data Analysis, 2009, vol. 53, issue 11, 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.

Date: 2009
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