Computing phylogenetic signal

I have posted a new function to compute phylogenetic signal for continuous traits using two methods: the lambda method of Pagel (1999) and Blomberg et al. (2003)'s K-statistic. Rich Glor already created a very helpful wiki page on how to do this in R using several different functions. My function, phylosig() (code here), should make this even easier. With phylosig() you can specify method (presently either "K" or "lambda") and optionally return a P-value for either the randomization test of Blomberg et al. or a likelihood ratio test against the null hypothesis that lambda=0.

For instance, after loading our function from source, to compute K and conduct a hypothesis test of the null hypothesis of no signal we just type:

> phylosig(tree,x,test=TRUE)
$K
[1] 1.053583

$P
[1] 0.001

By default, the function uses method="K" and nsim=1000.

Next, we can also estimate lambda using maximum likelihood:

> phylosig(tree,x,method="lambda",test=TRUE)
$lambda
[1] 0.9999339

$logL
[1] -132.7309

$P
[1] 0

Now, for comparison, let's simulate data with no phylogenetic signal:

> x<-rnorm(100); names(x)<-tree$tip.label
> phylosig(tree,x,test=TRUE)
$K
[1] 0.1020861

$P
[1] 0.426

> phylosig(tree,x,method="lambda",test=TRUE)
$lambda
[1] 6.610696e-05

$logL
[1] -138.0889

$P
[1] 1

Cool. Please check out the function (on my R-phylogenetics page) and let me know how it works.