On a Relation between Principal Components and Regression Analysis
The American StatisticianPublished 1 November 1999
Jyh‐Cherng Jong, Samuel Kotz
Citations22
SJR quartileQ1
SJR score0.78
SNIP1.50
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
A regression approach to principal component analysis is presented in this note. We provide an alternative interpretation of principal components that illustrates the relation between the extra sum of squares in regression analysis and the eigenvalues associated with the principal components.
Keywords
MathematicsAgricultural and Biological Sciences
BiometricsApplied Multivariate Statistical Analysis.
11,424 Citations1988Andrea Johnson, Dean W. Wichern
The Economic JournalMathematical Methods of Statistics.
6,007 Citations1947R. C. Geary, H. Leslie Cramer
Principal Components Analysis
2,664 Citations1989George H. Dunteman
The use and interpretation of principal component analysis in applied research
1,141 Citations1964C. Radhakrishhna Rao
Journal of the American Statistical AssociationCommon Principal Components and Related Multivariate Models.
481 Citations1990Robert J. Boik, Bernhard Flury
The Annals of Mathematical StatisticsAn Optimal Property of Principal Components
23 Citations1965J. N. Darroch