R: Bayesian MCMC method for identifying exceptional phenotypic...

evol.rate.mcmc {phytools}

R Documentation

Bayesian MCMC method for identifying exceptional phenotypic diversification in a phylogeny

Description

This function takes a phylogenetic tree and data for a single continuously valued character and uses a Bayesian MCMC approach to identify the phylogenetic location of a shift in the evolutionary rate through time.

Usage

evol.rate.mcmc(tree, x, ngen=10000, control=list())

Arguments

`tree`	a phylogenetic tree in `"phylo"` format.
`x`	a vector of tip values for species; `names(x)` should be the species names.
`ngen`	an optional integer value indicating the number of generations for the MCMC.
`control`	a list of control parameters containing the following elements: `sig1`: starting value for σ(1)^2; `sig2`: starting value for σ(2)^2; `a`: starting value for a; `sd1`: standard deviation for the normal proposal distribution for σ(1)^2; `sd2`: standard deviation for the normal proposal distribution for σ(2)^2; `kloc`: scaling parameter for tree move proposals - 1/λ for the reflected exponential distribution; `sdlnr`: standard deviation on the log-normal prior on σ(1)^2/σ(2)^2; `rand.shift`: probability of proposing a random shift in the tree (improves mixing); `print`: print frequency for the MCMC; `sample`: sample frequency.

Details

Default values of control are given in Revell et al. (2012).

Value

A list with the following components:

`mcmc`	results from the MCMC run.
`tips`	list of stips in rate σ(1)^2 for each sampled generation of MCMC (to polarize the rate shift).

Author(s)

Liam Revell liam.revell@umb.edu

References

Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol., 3, 217-223.

Revell, L. J., D. L. Mahler, P. Peres-Neto, and B. D. Redelings. (2012) A new method for identifying exceptional phenotypic diversification. Evolution, 66, 135-146.