ape (version 1.8-4)

mlphylo: Estimating Phylogenies by Maximum Likelihood

Description

mlphylo estimates a phylogenetic tree by maximum likelihood given a set of DNA sequences. The model of evolution is specified with the function DNAmodel.

logLik, deviance, and AIC are generic functions used to extract the log-likelihood, the deviance (-2*logLik), or the Akaike information criterion of a tree. If no such values are available, NULL is returned.

Usage

mlphylo(model = DNAmodel(), x, phy, search.tree = FALSE, quiet = FALSE)
## S3 method for class 'phylo':
logLik(object, ...)
## S3 method for class 'phylo':
deviance(object, ...)
## S3 method for class 'phylo':
AIC(object, ..., k = 2)

Arguments

Value

an object of class "phylo" with branch lengths as estimated by the function. There are two additional attributes:loglikthe maximum log-likelihood.parathe estimated parameters for each partition.

Details

The present version is a pre-alpha release. All comments, suggestions, bug reports, are warmly welcome.

The model specified by DNAmodel is fitted using the standard ``pruning'' algorithm of Felsenstein (1981). An algorithm for the estimation of tree topology is under development, and will be released when ready.

The implementation of the inter-sites variation in substitution rates follows the methodology developed by Yang (1994).

The difference among partitions is parametrized with a contrast parameter (denoted $\xi$) that specifies the contrast in mean susbtitution rate among the partitions. This methodology is inspired from one introduced by Yang (1996).

The substitution rates are indexed column-wise in the rate matrix: the first rate is set to one.

References

Felsenstein, J. (1981) Evolutionary trees from DNA sequences: a maximum likelihood approach. Journal of Molecular Evolution, 17, 368--376.

Yang, Z. (1994) Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: approximate methods. Journal of Molecular Evolution, 39, 306--314.

Yang, Z. (1996) Maximum-likelihood models for combined analyses of multiple sequence data. Journal of Molecular Evolution, 42, 587--596.

See Also

DNAmodel, nj, read.dna, summary.phylo