Data from: Effective online Bayesian phylogenetics via sequential Monte Carlo with guided proposals

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关键词：

phylogenetics;sequential Monte Carlo;Online Inference;Bayesian inference

DOI：

doi:10.5061/dryad.n7n85

摘要：

led sequential Monte Carlo (SMC) to conduct online inference, wherein new data can be continuously incorporated to update the estimate of the posterior probability distributi

Data from: Infectious disease dynamics inferred from genetic data via sequential Monte Carlo

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关键词：

sequential Monte Carlo;HIV;maximum likelihood;Virus evolution;Phylodynamics;iterated filtering

DOI：

doi:10.5061/dryad.3634m

摘要：

, Michigan. In a supplement, we prove that our approach is a valid sequential Monte Carlo algorithm. While we focus on how these methods may be applied

Data from: Phylogenetic signal and noise: predicting the power of a data set to resolve phylogeny

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关键词：

Site;noise;saturation;Rate;Informativeness;phylogeny;marker;information;polytomy;signal;parsimony;Locus;Power;Experimental design;resolution

DOI：

doi:10.5061/dryad.61cg073t

摘要：

internodes. We develop and implement a Monte Carlo approach to estimating power to resolve as well as deriving a nearly equivalent, faster deterministi

Data from: Bayes factors unmask highly variable information content, bias, and extreme influence in phylogenomic analyses

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关键词：

information content;Bayes factors;Bias;turtles;ultraconserved elements;amniotes;posterior probability;phylogenomics;Expressed Sequence Tags;Negative Constraints;ortholog

DOI：

doi:10.5061/dryad.8gm85

摘要：

h as Markov chain Monte Carlo estimates of posterior probabilities). Bayes factors reveal important, previously hidden, differences across six “phylogenomic” data sets collecte