A Simple Rule for the Selection of Principal Components
Communication in Statistics- Theory and MethodsPublished 4 January 2003
Dimitris Karlis, Gilbert Saporta, Antonis Spinakis
Citations93
SJR quartileQ3
SJR score0.46
SNIP1.02
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
International audience
Keywords
Agricultural and Biological SciencesMathematicsDecision Sciences
An Introduction to the Bootstrap
39,744 Citations1994Bradley Efron, Robert Tibshirani
Multivariate Behavioral ResearchThe Scree Test For The Number Of Factors
13,510 Citations1966Raymond B. Cattell
PsychometrikaA Rationale and Test for the Number of Factors in Factor Analysis
8,602 Citations1965John L. Horn
It is suggested that if Guttman's latent-root-one lower bound estimate for the rank of a correlation matrix is accepted as a psychometric upper bound, then the rank for a sample matrix should be estimated by subtracting out the component in the latent roots which can be attributed to sampling error.
TechnometricsA User's Guide to Principal Components
3,347 Citations1993Stefan D. Leigh, J. Edward Jackson
Principal Components Analysis
2,664 Citations1989George H. Dunteman
TechnometricsCross-Validatory Estimation of the Number of Components in Factor and Principal Components Models
2,496 Citations1978Svante Wold
PsychometrikaDetermining the Number of Components from the Matrix of Partial Correlations
2,425 Citations1976Wayne F. Velicer
An alternative solution which employs a matrix of partial correlations is considered, which gives an exact stopping point, has a direct operational interpretation, and can be applied to any type of component analysis.
The Annals of Mathematical StatisticsAsymptotic Theory for Principal Component Analysis
1,153 Citations1963T. W. Anderson
TechnometricsCross-Validatory Estimation of the Number of Components in Factor and Principal Components Models
578 Citations1978Svante Wold
BiometricsStatistical Factor Analysis and Related Methods: Theory and Applications.
402 Citations1997Ian T. Jolliffe, A. Basilevsky
The Annals of StatisticsBootstrap Tests and Confidence Regions for Functions of a Covariance Matrix
256 Citations1985Rudolf Beran, Muni S. Srivastava
The Annals of StatisticsDistinctness of the Eigenvalues of a Quadratic form in a Multivariate Sample
162 Citations1973Masashi Okamoto
BiometrikaAsymptotic distribution of the sample roots for a nonnormal population
124 Citations1976Christine Waternaux
Australian Journal of StatisticsASYMPTOTIC THEORY FOR PRINCIPAL COMPONENT ANALYSIS: NON‐NORMAL CASE1
57 Citations1977A. W. Davis
The Annals of StatisticsA Class of Asymptotic Tests for Principal Component Vectors
28 Citations1983David E. Tyler
The Annals of StatisticsThe Asymptotic Distribution of Principal Component Roots Under Local Alternatives to Multiple Roots
25 Citations1983David E. Tyler
The American StatisticianMultivariate Analysis of National Track Records
23 Citations1989Brian P. Dawkins
Research Quarterly American Alliance for Health Physical Education and RecreationFactor Analytical Study of Olympic Decathlon Data
16 Citations1977Michael Linden
Basic physical fitness or motor performance functions as expressed in decathlon data are indicated through a factor analytical approach, which indicates a four-factor pattern which is interpreted in terms of running speed, explosive arm strength, running endurance, and explosive leg strength.
