\name{sh.test}
\alias{sh.test}
\title{Shimodaira-Hasegawa Test}
\usage{
sh.test(..., x, model = DNAmodel(), B = 100)
}
\arguments{
  \item{...}{either a series of objects of class \code{"phylo"}
    separated by commas, or a list containing such objects.}
  \item{x}{a list or a matrix containing the (aligned) DNA sequences.}
  \item{model}{the model to be fitted to each tree (as an object of
    \code{"DNAmodel"}).}
  \item{B}{the number of bootstrap replicates.}
}
\description{
  This function computes the Shimodaira--Hasegawa test for a set of
  trees.
}
\details{
  The present implementation follows the original formulation of
  Shimodaira and Hasegawa (1999) with the difference that the bootstrap
  resampling is done on the original sequence data rather than the RELL
  method suggested by Shimodaira and Hasegawa.
}
\value{
  a numeric vector with the P-value associated with each tree given in
  \code{...}.
}
\references{
  Shimodaira, H. and Hasegawa, M. (1999) Multiple comparisons of
  log-likelihoods with applications to phylogenetic
  inference. \emph{Molecular Biology and Evolution}, \bold{16},
  1114--1116.
}
\author{Emmanuel Paradis \email{Emmanuel.Paradis@mpl.ird.fr}}
\seealso{
  \code{\link{mlphylo}}, \code{\link{DNAmodel}}
}
\examples{
data(woodmouse)
t1 <- nj(dist.dna(woodmouse))
t2 <- rtree(15, tip.label = t1$tip.label)
t3 <- rtree(15, tip.label = t1$tip.label)
### Are the NJ tree and two random tress significantly different?
\dontrun{sh.test(t1, t2, t3, x = woodmouse, B = 100)}
}
\keyword{models}