Shimodaira-Hasegawa Test

This function computes the Shimodaira–Hasegawa test for a set of trees.

Usage

SH.test(..., B = 10000, data = NULL, weight = NULL)

Arguments

...: either a series of objects of class "pml" separated by commas, a list containing such objects or an object of class "pmlPart" or a matrix containing the site-wise likelihoods in columns.
B: the number of bootstrap replicates.
data: an object of class "phyDat".
weight: if a matrix with site (log-)likelihoods is is supplied an optional vector containing the number of occurrences of each site pattern.

Value

a numeric vector with the P-value associated with each tree given in ....

References

Shimodaira, H. and Hasegawa, M. (1999) Multiple comparisons of log-likelihoods with applications to phylogenetic inference. Molecular Biology and Evolution, 16, 1114–1116.

Author

Klaus Schliep klaus.schliep@gmail.com

Examples


data(Laurasiatherian)
dm <- dist.logDet(Laurasiatherian)
tree1 <- NJ(dm)
tree2 <- unroot(upgma(dm))
fit1 <- pml(tree1, Laurasiatherian)
fit2 <- pml(tree2, Laurasiatherian)
fit1 <- optim.pml(fit1) # optimize edge weights
#> optimize edge weights:  -54807.68 --> -54290.26 
#> optimize edge weights:  -54290.26 --> -54290.26 
#> optimize edge weights:  -54290.26 --> -54290.26 
fit2 <- optim.pml(fit2)
#> optimize edge weights:  -55623.41 --> -54911.33 
#> optimize edge weights:  -54911.33 --> -54911.33 
#> optimize edge weights:  -54911.33 --> -54911.33 
# with pml objects as input
SH.test(fit1, fit2, B=1000)
#>      Trees      ln L Diff ln L p-value
#> [1,]     1 -54290.26    0.0000   0.498
#> [2,]     2 -54911.33  621.0767   0.000
# in real analysis use larger B, e.g. 10000

# with matrix as input
X <- matrix(c(fit1$siteLik, fit2$siteLik), ncol=2)
SH.test(X, weight=attr(Laurasiatherian, "weight"), B=1000)
#>      Trees      ln L Diff ln L p-value
#> [1,]     1 -54290.26    0.0000   0.492
#> [2,]     2 -54911.33  621.0767   0.000
if (FALSE) { # \dontrun{
example(pmlPart)
SH.test(sp, B=1000)
} # }