Commit 82972fd0 authored by Antoine Lucas's avatar Antoine Lucas
Browse files

new parameters

parent 49fc697f
\name{acp}
\alias{acp}
\alias{pca}
\alias{print.acp}
\title{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, ...)
}
\arguments{
\item{x}{Matrix / data frame}
\item{center}{a logical value indicating whether we center data}
\item{reduce}{a logical value indicating whether we "reduce" data i.e.
divide each column by standard deviation}
\item{wI,wV}{weigth vector for individuals / variables}
\item{\dots}{arguments to be passed to or from other methods.}
}
\value{
An object of class \bold{acp}
The object is a list with components:
\item{sdev}{the standard deviations of the principal components.}
\item{loadings}{the matrix of variable loadings (i.e., a matrix
whose columns contain the eigenvectors). This is of class
\code{"loadings"}: see \code{\link[stats]{loadings}} for its \code{print}
method.}
\item{scores}{if \code{scores = TRUE}, the scores of the supplied
data on the principal components.}
\item{eig}{Eigen values}
}
\details{
This function offer a variant of \code{\link[stats]{princomp}} and
\code{\link[stats]{prcomp}} functions, with a slightly different
graphic representation (see \code{\link{plot.acp}}).
}
\references{
A. Carlier
Analyse des données Multidimensionnelles
\url{http://www.lsp.ups-tlse.fr/Carlier/enseignement.html}
}
\examples{
data(lubisch)
lubisch <- lubisch[,-c(1,8)]
p <- acp(lubisch)
plot(p)
}
\keyword{multivariate}
\author{Antoine Lucas, \url{http://mulcyber.toulouse.inra.fr/projects/amap/}}
\seealso{\link{plot.acp},\link{acpgen}, \link[stats]{princomp} }
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