3 \title{Shimodaira-Hasegawa Test}
5 sh.test(..., x, model = DNAmodel(), B = 100)
8 \item{...}{either a series of objects of class \code{"phylo"}
9 separated by commas, or a list containing such objects.}
10 \item{x}{a list or a matrix containing the (aligned) DNA sequences.}
11 \item{model}{the model to be fitted to each tree (as an object of
13 \item{B}{the number of bootstrap replicates.}
16 This function computes the Shimodaira--Hasegawa test for a set of
20 The present implementation follows the original formulation of
21 Shimodaira and Hasegawa (1999) with the difference that the bootstrap
22 resampling is done on the original sequence data rather than the RELL
23 method suggested by Shimodaira and Hasegawa.
26 a numeric vector with the P-value associated with each tree given in
30 Shimodaira, H. and Hasegawa, M. (1999) Multiple comparisons of
31 log-likelihoods with applications to phylogenetic
32 inference. \emph{Molecular Biology and Evolution}, \bold{16},
35 \author{Emmanuel Paradis \email{Emmanuel.Paradis@mpl.ird.fr}}
37 \code{\link{mlphylo}}, \code{\link{DNAmodel}}
41 t1 <- nj(dist.dna(woodmouse))
42 t2 <- rtree(15, tip.label = t1$tip.label)
43 t3 <- rtree(15, tip.label = t1$tip.label)
44 ### Are the NJ tree and two random tress significantly different?
45 \dontrun{sh.test(t1, t2, t3, x = woodmouse, B = 100)}