amap (version 0.7-3)

acp: Principal component analysis

Description

Principal component analysis

Usage

acp(x,center=TRUE,reduce=TRUE,wI=rep(1,nrow(x)),wV=rep(1,ncol(x)))
pca(x,center=TRUE,reduce=TRUE,wI=rep(1,nrow(x)),wV=rep(1,ncol(x)))
print.acp(x, ...)

Value

An object of class acp The object is a list with components:sdevthe standard deviations of the principal components.loadingsthe matrix of variable loadings (i.e., a matrix whose columns contain the eigenvectors). This is of class "loadings": see loadings for its print method.scoresif scores = TRUE, the scores of the supplied data on the principal components.eigEigen values

Details

This function offer a variant of princomp and prcomp functions, with a slightly different graphic representation (see plot.acp).

References

A. Carlier Analyse des donn�es Multidimensionnelles http://www.lsp.ups-tlse.fr/Carlier/enseignement.html

See Also

plot.acp,acpgen, princomp

Examples

data(lubisch)
lubisch <- lubisch[,-c(1,8)]
p <- acp(lubisch)
plot(p)