| componentAxis {nFactors} | R Documentation |
Principal Component Analysis With Only n First Components Retained
Description
The componentAxis function returns a principal component analysis
with the first n components retained.
Usage
componentAxis(R, nFactors = 2)
Arguments
R |
numeric: correlation or covariance matrix |
nFactors |
numeric: number of components/factors to retain |
Value
values |
numeric: variance of each component/factor retained |
varExplained |
numeric: variance explained by each component/factor retained |
varExplained |
numeric: cumulative variance explained by each component/factor retained |
loadings |
numeric: loadings of each variable on each component/factor retained |
Author(s)
Gilles Raiche
Centre sur les Applications des Modeles de
Reponses aux Items (CAMRI)
Universite du Quebec a Montreal
raiche.gilles@uqam.ca
References
Kim, J.-O. and Mueller, C. W. (1978). Introduction to factor analysis. What it is and how to do it. Beverly Hills, CA: Sage.
Kim, J.-O. and Mueller, C. W. (1987). Factor analysis. Statistical methods and practical issues. Beverly Hills, CA: Sage.
See Also
principalComponents,
iterativePrincipalAxis, rRecovery
Examples
# .......................................................
# Example from Kim and Mueller (1978, p. 10)
# Simulated sample: lower diagnonal
R <- matrix(c( 1.000, 0.560, 0.480, 0.224, 0.192, 0.16,
0.560, 1.000, 0.420, 0.196, 0.168, 0.14,
0.480, 0.420, 1.000, 0.168, 0.144, 0.12,
0.224, 0.196, 0.168, 1.000, 0.420, 0.35,
0.192, 0.168, 0.144, 0.420, 1.000, 0.30,
0.160, 0.140, 0.120, 0.350, 0.300, 1.00),
nrow=6, byrow=TRUE)
# Factor analysis: Selected principal components - Kim and Mueller
# (1978, p. 20)
componentAxis(R, nFactors=2)
# .......................................................