Postprocessing of genealogical trees.

Abstract:

:We consider inference for demographic models and parameters based upon postprocessing the output of an MCMC method that generates samples of genealogical trees (from the posterior distribution for a specific prior distribution of the genealogy). This approach has the advantage of taking account of the uncertainty in the inference for the tree when making inferences about the demographic model and can be computationally efficient in terms of reanalyzing data under a wide variety of models. We consider a (simulation-consistent) estimate of the likelihood for variable population size models, which uses importance sampling, and propose two new approximate likelihoods, one for migration models and one for continuous spatial models.

journal_name

Genetics

journal_title

Genetics

authors

Meligkotsidou L,Fearnhead P

doi

10.1534/genetics.107.071910

subject

Has Abstract

pub_date

2007-09-01 00:00:00

pages

347-58

issue

1

eissn

0016-6731

issn

1943-2631

pii

genetics.107.071910

journal_volume

177

pub_type

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