phangorn (version 1.7-4)

pmlPart: Partition model.

Description

Model to estimate phylogenies for partitioned data.

Usage

pmlPart(formula, object, control = pml.control(epsilon=1e-8, maxit=10, trace=1), model=NULL, ...)

Arguments

formula

a formula object (see details).

object

an object of class pml or a list of objects of class pml .

control

A list of parameters for controlling the fitting process.

model

A vector containing the models containing a model dor each partition.

...

Further arguments passed to or from other methods.

Value

• kcluster returns a list with elements
• logLik
  log-likelihood of the fit
• trees
  a list of all trees during the optimization.
• object
  an object of class "pml" or "pmlPart"

Details

The formula object allows to specify which parameter get optimized. The formula is generally of the form edge + bf + Q ~ rate + shape + ..., on the left side are the parameters which get optimized over all partitions, on the right the parameter which are optimized specific to each partition. The parameters available are "nni", "bf", "Q", "inv", "shape", "edge", "rate". Each parameters can be used only once in the formula. "rate" and "nni" are only available for the right side of the formula. For partitions with different edge weights, but same topology, pmlPen can try to find more parsimonious models (see example).

See Also

pml,pmlCluster,pmlMix,SH.test

Examples

data(yeast)
dm <- dist.logDet(yeast)
tree <- NJ(dm)
fit <- pml(tree,yeast)
fits <- optim.pml(fit)

weight=xtabs(~ index+genes,attr(yeast, "index"))[,1:10]

sp <- pmlPart(edge ~ rate + inv, fits, weight=weight)
sp

sp2 <- pmlPart(~ edge + inv, fits, weight=weight)
sp2
AIC(sp2)

sp3 <- pmlPen(sp2, lambda = 2) 
AIC(sp3)