Markov genealogy processes: code Article Swipe
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· 2021
· Open Access
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· DOI: https://doi.org/10.5281/zenodo.5758899
· OA: W4200418173
Codes and data files for the figures displayed in "Markov genealogy processes", (<em>Theoretical Population Biology </em><strong>143: </strong>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.
