Bayesian Phylogenetic Inference Using a Combinatorial Sequential Monte Carlo Method

The application of Bayesian methods to large-scale phylogenetics problems is increasingly limited by computational issues, motivating the development of methods that can complement existing Markov chain Monte Carlo (MCMC) schemes. Sequential Monte Carlo (SMC) methods are approximate inference algori...

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Veröffentlicht in:	Journal of the American Statistical Association 2015-12, Vol.110 (512), p.1362-1374
Hauptverfasser:	Wang, Liangliang, Bouchard-Côté, Alexandre, Doucet, Arnaud
Format:	Artikel
Sprache:	eng
Schlagworte:	algorithms Applications and Case Studies Bayesian analysis Bayesian inference Bayesian method Markov analysis Markov chain Monte Carlo method Monte Carlo simulation Particle Markov chain Monte Carlo Phylogenetics phylogeny Poset Sampling Sequential Monte Carlo Statistics Time series time series analysis
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