Markov genealogy processes: code Article Swipe

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genealogy code (set theory) markov chain computer science history programming language set (abstract data type) machine learning

Aaron A. King , Qianying Lin , Edward L. Ionides ·

YOU? · · 2021 · Open Access · · DOI: https://doi.org/10.5281/zenodo.5758899 · OA: W4200418173

Codes and data files for the figures displayed in "Markov genealogy processes", (Theoretical Population Biology 143: 77-91, 2022, doi: 10.1016/j.tpb.2021.11.003). See also the arXiv preprint. 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.