\name{componentAxis}
\alias{componentAxis}
\title{ Principal Component Analysis With Only n First Components Retained}

\description{
The \code{componentAxis} function returns a principal component analysis
with the first \emph{n} components retained.
}

\usage{
componentAxis(R, nFactors=2)
}

\arguments{
\item{R}{        numeric: correlation or covariance matrix}
\item{nFactors}{ numeric: number of components/factors to retain}
}

\value{
\item{values}{       numeric: variance of each component/factor retained }
\item{varExplained}{ numeric: variance explained by each component/factor retained }
\item{varExplained}{ numeric: cumulative variance explained by each component/factor retained }
}

\references{
Kim, J.-O. and Mueller, C. W. (1978). \emph{Introduction to factor analysis. What it
is and how to do it}. Beverly Hills, CA: Sage.

Kim, J.-O. and Mueller, C. W. (1987). \emph{Factor analysis. Statistical methods and
practical issues}. Beverly Hills, CA: Sage.
}

\seealso{
}

\author{
Gilles Raiche \cr
Centre sur les Applications des Modeles de Reponses aux Items (CAMRI) \cr
Universite du Quebec a Montreal\cr
\email{raiche.gilles@uqam.ca}, \url{http://www.er.uqam.ca/nobel/r17165/}
}

\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)

# .......................................................
}

\keyword{ multivariate }