\name{leverage}
\title{Extract leverages of a PCA model}
\description{The leverages of PCA model indicate how much influence each
observation has on the PCA model. Observations with high leverage
has caused the principal components to rotate towards them. It can
be used to extract both "unimportant" observations as well as
picking potential outliers.}
\details{Defined as \eqn{Tr(T(T'T)^{-1}T')}{Tr(T(T'T)^(-1)T')}}
\value{The observation leverages as a numeric vector}
\references{Introduction to Multi- and Megavariate Data Analysis
using Projection Methods (PCA and PLS), L. Eriksson, E. Johansson,
N. Kettaneh-Wold and S. Wold, Umetrics 1999, p. 466}
\keyword{multivariate}
\alias{leverage}
\alias{leverage,pcaRes-method}
\author{Henning Redestig}
\arguments{\item{object}{a \code{pcaRes} object}}
\examples{data(iris)
pcIr <- pca(iris[,1:4])
## versicolor has the lowest leverage
with(iris, plot(leverage(pcIr)~Species))}