Markov Genealogy Processes
Probability
2022-01-26 v4 Populations and Evolution
Quantitative Methods
Applications
Methodology
Abstract
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.
Keywords
Cite
@article{arxiv.2105.12730,
title = {Markov Genealogy Processes},
author = {Aaron A. King and Qianying Lin and Edward L. Ionides},
journal= {arXiv preprint arXiv:2105.12730},
year = {2022}
}