title: Full reconstruction of Markov models on evolutionary trees: identifiability and consistency.
abstract: A Markov model of evolution of characters on a phylogenetic tree consists of a tree topology together with a specification of probability transition matrices on the edges of the tree. Previous work has shown that, under mild conditions, the tree topology may be reconstructed, in the sense that the topology is identifiable from knowledge of the joint distribution of character states at pairs of terminal nodes of the tree. Also, the method of maximum likelihood is statistically consistent for inferring the tree topology. In this article we answer the analogous questions for reconstructing the full model, including the edge transition matrices. Under mild conditions, such full reconstruction is achievable, not by using pairs of terminal nodes, but rather by using triples of terminal nodes. The identifiability result generalizes previous results that were restricted either to characters having two states or to transition matrices having special structure. The proof develops matrix relationships that may be exploited to identify the model. We also use the identifiability result to prove that the method of maximum likelihood is consistent for reconstructing the full model.
authors.affiliation: Department of Statistics, Yale University, New Haven, CT 06520-8290, USA.
authors.forename: J T
authors.initials: JT
authors.lastname: Chang
mesh_terms: D000818:Animals; D005075:Biological Evolution; D008390:Markov Chains; D008954:Models, Biological