The King Laboratory
of Theoretical Ecology & Evolution
at the University of Michigan

Markov genealogy processes

A. A. King, Q. Lin, and E. L. Ionides
Theoretical Population Biology 143:  77–91, 2022.
Markov genealogy processes for phylodynamic inference.

We construct a family of genealogy-valued Markov processes that are induced by a continuous-time Markov population process. We derive exact expressions for the likelihood of a given genealogy conditional on the history of the underlying population process. These lead to a nonlinear filtering equation which can be used to design efficient Monte Carlo inference algorithms. We demonstrate these calculations with several examples. Existing full-information approaches for phylodynamic inference are special cases of the theory.

The official version of the paper is here.   Please contact Prof. King if you'd like a reprint.

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