Abbreviated Journal Title
Stat. Sin.
Keywords
Dimension reduction; principal components; regression; spherically; symmetric distribution; DIMENSION REDUCTION; FISHER LECTURE; Statistics & Probability
Abstract
Principal component regression has been perceived as a remedy for multi-collinearity. Cook (2007) suggested that principal components and related methodology actually play a broader role than previously thought. Recently, Artemiou and Li (2009) provided a probabilistic explanation of the phenomenon that the response is often highly correlated with the leading principal components of the predictors. This article reinforces the previous results and offers an alternative perspective.
Journal Title
Statistica Sinica
Volume
21
Issue/Number
2
Publication Date
1-1-2011
Document Type
Article
Language
English
First Page
741
Last Page
747
WOS Identifier
ISSN
1017-0405
Recommended Citation
Ni, Liqiang, "Principal Component Regression Revisited" (2011). Faculty Bibliography 2010s. 7077.
https://stars.library.ucf.edu/facultybib2010/7077
Comments
Authors: contact us about adding a copy of your work at STARS@ucf.edu