Abstract
AbstractThis chapter describes the pruning algorithm for calculating the likelihood on a tree, as well as extensions under complex substitution models, including the gamma and covarion models of rate variation among sites and lineages. It discusses numerical optimization algorithms for maximum likelihood estimation. It provides a critical assessment of methods for reconstructing ancestral states for both molecular sequences and morphological characters. Finally the chapter discusses model selection in phylogenetics using the likelihood ratio test (LRT) and information criteria such as the Akaike information criterion (AIC) and Bayesian information criterion (BIC).
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