Properties of Markov Chain Monte Carlo Performance across Many Empirical Alignments

Nearly all current Bayesian phylogenetic applications rely on Markov chain Monte Carlo (MCMC) methods to approximate the posterior distribution for trees and other parameters of the model. These approximations are only reliable if Markov chains adequately converge and sample from the joint posterior...

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Detalles Bibliográficos
Autores principales: Harrington, Sean M, Wishingrad, Van, Thomson, Robert C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Methods
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042746/
https://www.ncbi.nlm.nih.gov/pubmed/33185685
http://dx.doi.org/10.1093/molbev/msaa295

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8042746/
https://www.ncbi.nlm.nih.gov/pubmed/33185685
http://dx.doi.org/10.1093/molbev/msaa295

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