componentAxis | R Documentation |
The componentAxis
function returns a principal component analysis
with the first n components retained.
componentAxis(R, nFactors = 2)
R |
numeric: correlation or covariance matrix |
nFactors |
numeric: number of components/factors to retain |
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 |
Gilles Raiche
Centre sur les Applications des Modeles de
Reponses aux Items (CAMRI)
Universite du Quebec a Montreal
raiche.gilles@uqam.ca
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.
principalComponents
,
iterativePrincipalAxis
, rRecovery
# ....................................................... # 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) # .......................................................
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