\name{KLdist.matrix}
\alias{KLdist.matrix}
\alias{KLdist.matrix,matrix-method}
\alias{KLdist.matrix,list-method}
\alias{KLdist.matrix,ExpressionSet-method}
\title{Discrete version of Kullback-Leibler Distance (KLD)}
\description{
Calculate the KLD by binning continuous data.
}
\usage{
KLdist.matrix(x, \dots)
}
\arguments{
  \item{x}{n by p matrix or ExpressionSet; if x is an ExpressionSet,then
    the values returned by the \code{exprs} function are used.}
  \item{\dots}{arguments passed to \code{KLdist.matrix}:
    \item{nbin}{number of bins to calculate discrete probabilities; default is 10.}
    \item{symmetrize}{if TRUE, then symmetrize; default is FALSE.}
    \item{diag}{if TRUE, then the diagonal of the distance matrix will be displayed; default is FALSE.}
    \item{upper}{if TRUE, then the upper triangle of the distance matrix will be displayed; default is FALSE.}
    \item{sample}{for ExpressionSet methods: if TRUE, then the distances are computed between samples,
    otherwise, between genes.}
  }
}
\details{
  The data are binned, and then the KL distance between the two discrete
  distributions is computed and used.

  The list method is meant for use when samples sizes are unequal.
}
\value{
Pairwsie KLD object
}
\author{Beiying Ding}
\seealso{\code{\link{cor.dist}}, \code{\link{spearman.dist}}, 
  \code{\link{tau.dist}},\code{\link{euc}},
  \code{\link{man}},\code{\link{KLD.matrix}},\code{\link{mutualInfo}}}
\examples{
 x <- matrix(rnorm(100), nrow = 5)
 KLdist.matrix(x, symmetrize = TRUE, nbin = 3) 
}
\keyword{manip}