phytools (version 0.7-70)

anc.trend: Ancestral character estimation with a trend

Description

This function estimates the evolutionary parameters and ancestral states for Brownian evolution with directional trend.

Usage

anc.trend(tree, x, maxit=2000)

Arguments

tree

an object of class "phylo".

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.

Value

An object of class "anc.trend" with the following components:

ace

a vector with the ancestral states.

mu

a trend parameter per unit time.

sig2

the variance of the BM process, \(\sigma^2\).

logL

the log-likelihood.

convergence

the value of $convergence returned by optim() (0 is good).

Details

Note that this will generally only work and produce sensible results for a phylogeny with some non-contemporary tips (i.e., a tree with some fossil species). The function uses optim with method= "L-BFGS-B"; however optimization is only constrained for the sig2 which must be >0.

References

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

See Also

ace, anc.Bayes, anc.ML, optim

Examples

# NOT RUN {
## simulate tree & data using fastBM with a trend (m!=0)
tree<-rtree(n=26,tip.label=LETTERS)
x<-fastBM(tree,mu=4,internal=TRUE)
a<-x[as.character(1:tree$Nnode+Ntip(tree))]
x<-x[tree$tip.label]
## fit no trend model
fit.bm<-anc.ML(tree,x,model="BM")
print(fit.bm)
## fit trend model
fit.trend<-anc.trend(tree,x)
print(fit.trend)
## compare trend vs. no-trend models & estimates
AIC(fit.bm,fit.trend)
layout(matrix(c(3,4,1,2,5,6),3,2,byrow=TRUE),
    heights=c(1.5,3,1.5),widths=c(3,3))
xlim<-ylim<-range(c(a,fit.bm$ace,
    fit.trend$ace))
plot(a,fit.bm$ace,pch=19,
    col=make.transparent("blue",0.5),
    xlab="true ancestral states",
    ylab="ML estimates",
    main=paste("Comparison of true and estimated",
    "\nstates under a no-trend model"),font.main=3,
    cex.main=1.2,bty="l",cex=1.5,
    xlim=xlim,ylim=ylim)
lines(xlim,ylim,lty="dotted")
plot(a,fit.trend$ace,pch=19,
    col=make.transparent("blue",0.5),
    xlab="true ancestral states",
    ylab="ML estimates",
    main=paste("Comparison of true and estimated",
    "\nstates under a trend model"),font.main=3,
    cex.main=1.2,bty="l",cex=1.5,
    xlim=xlim,ylim=ylim)
lines(xlim,ylim,lty="dotted")
par(mfrow=c(1,1))
# }