phytools (version 0.1-6)

brownie.lite: Likelihood test for rate variation

Description

This function takes a modified "phylo" object with a mapped binary or multistate trait (see read.simmap) and data for a single continuously valued character. It then fits the Brownian rate variation ("noncensored") model of O'Meara et al. (2006; Evolution). This is also the basic model implemented in Brian O'Meara's "Brownie" program.

Usage

brownie.lite(tree,x,maxit=2000,test="chisq",nsim=100)

Arguments

tree

a phylogenetic tree in modified "phylo" format (see read.simmap and make.simmap).

x

a vector of tip values for species; names(x) should be the species names.

maxit

an optional integer value indicating the maximum number of iterations for optimization - may need to be increased for large trees.

test

an optional string indicating the method for hypothesis testing - options are "chisq" or "simulation".

nsim

number of simulations (only used if test="simulation").

Value

• a list with the following components:
• sig2.single
  is the rate for a single rate model - this is usually the "null" model.
• a.single
  is the estimated state at the root node for the single rate model.
• var.single
  variance on the single rate estimator - obtained from the Hessian.
• logL1
  log-likelihood of the single-rate model.
• k1
  number of parameters in the single rate model (always 2).
• sig2.multiple
  is a length p (for p rates) vector of BM rates from the multi-rate model.
• a.multiple
  is the estimated state at the root node for the multi-rate model.
• var.multiple
  p x p variance-covariance matrix for the p rates - the square-roots of the diagonals should give the standard error for each rate.
• logL.multiple
  log-likelihood of the multi-rate model.
• k2
  number of parameters in the multi-rate model (p+1).
• P.chisq
  P-value for a likelihood ratio test against the Chi-squared distribution; or
• P.sim
  P-value for a likelihood ratio test agains a simulated null distribution.
• convergence
  logical value indicating if the likelihood optimization converged.

References

O'Meara, B. C., C. Ane, M. J. Sanderson, and P. C. Wainwright. 2006. Testing for different rates of continuous trait evolution using likelihood. Evolution, 60, 922--933.

See Also

brownieREML, evol.vcv