Counting labeled transitions in continuous-time Markov models of evolution

VN Minin, MA Suchard - Journal of mathematical biology, 2008 - Springer
Journal of mathematical biology, 2008Springer
Counting processes that keep track of labeled changes to discrete evolutionary traits play
critical roles in evolutionary hypothesis testing. If we assume that trait evolution can be
described by a continuous-time Markov chain, then it suffices to study the process that
counts labeled transitions of the chain. For a binary trait, we demonstrate that it is possible to
obtain closed-form analytic solutions for the probability mass and probability generating
functions of this evolutionary counting process. In the general, multi-state case we show how …
Abstract
Counting processes that keep track of labeled changes to discrete evolutionary traits play critical roles in evolutionary hypothesis testing. If we assume that trait evolution can be described by a continuous-time Markov chain, then it suffices to study the process that counts labeled transitions of the chain. For a binary trait, we demonstrate that it is possible to obtain closed-form analytic solutions for the probability mass and probability generating functions of this evolutionary counting process. In the general, multi-state case we show how to compute moments of the counting process using an eigen decomposition of the infinitesimal generator, provided the latter is a diagonalizable matrix. We conclude with two examples that demonstrate the utility of our results.
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