Author: King, Aaron A.; Lin, Qianying; Ionides, Edward L.
Title: Markov Genealogy Processes Cord-id: 1vgo4xcx Document date: 2021_5_26
ID: 1vgo4xcx
Snippet: 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 version of the nonlinear filtering equation, which can be used to design efficient Monte Carlo inference algorithms. Existing full-information approaches for phylodynamic inference are special cases of the theory.
Document: 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 version of the nonlinear filtering equation, which can be used to design efficient Monte Carlo inference algorithms. Existing full-information approaches for phylodynamic inference are special cases of the theory.
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