\name{ps.cluster}
\alias{ps.cluster}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Function to compute the prediction strength of a clustering model
}
\description{
This function computes the prediction strength of a clustering model as published in R. Tibshirani and G. Walther 2005.
}
\usage{
ps.cluster(cl.tr, cl.ts, na.rm = FALSE)
}
%- maybe also 'usage' for other objects documented here.
\arguments{
  \item{cl.tr}{
Clusters membership as defined by the original clustering model, i.e. the one that was not fitted on the dataset of interest.
}
  \item{cl.ts}{
Clusters membership as defined by the clustering model fitted on the dataset of interest.
}
  \item{na.rm}{
\code{TRUE} if missing values should be removed, \code{FALSE} otherwise.
}
}
%%\details{
%%  ~~ If necessary, more details than the description above ~~
%%}
\value{
%%  ~Describe the value returned
%%  If it is a LIST, use
  \item{ps }{the overall prediction strength (minimum of the prediction strengths at cluster level).}
  \item{ps.cluster }{Prediction strength for each cluster}
  \item{ps.individual }{Prediction strength for each sample.}
}
\references{
R. Tibshirani and G. Walther (2005) "Cluster Validation by Prediction Strength", \emph{Journal of Computational and Graphical Statistics}, \bold{14}(3):511--528.
}
\author{
Benjamin Haibe-Kains
}
%%\note{
%%  ~~further notes~~
%%}

%% ~Make other sections like Warning with \section{Warning }{....} ~

%%\seealso{
%% ~~objects to See Also as \code{\link{help}}, ~~~
%%}
\examples{
## load SSP signature published in Sorlie et al. 2003
data(ssp2003)
## load NKI data
data(nki)
## SP2003 fitted on NKI
ssp2003.2nki <- intrinsic.cluster(data=data.nki, annot=annot.nki,
  do.mapping=TRUE, std="robust",
  intrinsicg=ssp2003$centroids.map[ ,c("probe", "EntrezGene.ID")],
  number.cluster=5, mins=5, method.cor="spearman",
  method.centroids="mean", verbose=TRUE)
## SP2003 published in Sorlie et al 2003 and applied in VDX
ssp2003.nki <- intrinsic.cluster.predict(sbt.model=ssp2003,
  data=data.nki, annot=annot.nki, do.mapping=TRUE, verbose=TRUE)
## prediction strength of sp2003 clustering model
ps.cluster(cl.tr=ssp2003.2nki$subtype, cl.ts=ssp2003.nki$subtype,
  na.rm = FALSE)
}
% Add one or more standard keywords, see file 'KEYWORDS' in the
% R documentation directory.
\keyword{ clustering }