acp {amap}R Documentation

Principal component analysis

Description

Principal component analysis / Analyse en composantes principales

Usage

acp(x,center=TRUE,reduce=TRUE)
pca(x,center=TRUE,reduce=TRUE)
print.acp(x, ...) 

Arguments

x Matrix / data frame
center a logical value indicating whether we center data
reduce a logical value indicating whether we "reduce" data i.e. divide each column by standard deviation
... arguments to be passed to or from other methods.

Value

An object of class acp The object is a list with components:

sdev the standard deviations of the principal components.
loadings the matrix of variable loadings (i.e., a matrix whose columns contain the eigenvectors). This is of class "loadings": see loadings for its print method.
scores if scores = TRUE, the scores of the supplied data on the principal components.
eig Eigen values

Author(s)

Antoine Lucas, http://antoinelucas.free.fr/amap

References

A. Carlier Analyse des données 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)

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