1982/01/01 by Ian T. Jolliffe · 5 citations
Mathematics · Chemistry · #Advanced Statistical Methods and Models #Spectroscopy and Chemometric Analyses #Statistical and numerical algorithms
paper · doi:10.2307/2348005
openalex publication_date 1982/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The use of principal components in regression has received a lot of attention in the literature in the past few years, and the topic is now beginning to appear in textbooks. Along with the use of principal component regression there appears to have been a growth in the misconception that the principal components with small eigenvalues will very rarely be of any use in regression. The purpose of this note is to demonstrate that these components can be as important as those with large variance. This is illustrated with four examples, three of which have already appeared in the literature.