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Data from: An efficient independence sampler for updating branches in Bayesian Markov chain Monte Carlo sampling of phylogenetic trees
负责人:
关键词:
independence sampling;proposal efficiency;Newton-Raphson optimization;tree topology proposals;Markov chain Monte Carlo;phylogenetics;Bayesian inference
DOI:
doi:10.5061/dryad.63pm5
摘要:
y for topological convergence. Inconsistent performance gains indicate that branch updates are not the limiting factor in improving topological convergence for the cu
Data from: The behavior of Metropolis-coupled Markov chains when sampling rugged phylogenetic distributions
负责人:
关键词:
Metropolis coupling;Markov chain Monte Carlo;Bayesian;MC3;Tetrapoda
DOI:
doi:10.5061/dryad.584m3
摘要:
ated by regions of low posterior density. Markov chain Monte Carlo (MCMC) algorithms are the most widely used numerical method for generating samples from these
Data from: Evolutionary tracking is determined by differential selection on demographic rates and density dependence.
负责人:
关键词:
adaptive evolution;climate change
DOI:
doi:10.5061/dryad.w6m905qmg
摘要:
, and selection on density dependence. Using a continuous-time Markov chain model to describe the stochastic dynamics of the logistic model of population growth
Data from: Ancestral character estimation under the threshold model from quantitative genetics
负责人:
关键词:
Morphological Evolution;phylogenetics;Models\/Simulations;quantitative genetics
DOI:
doi:10.5061/dryad.4t157
摘要:
Markov chain Monte Carlo (MCMC) to sample the liabilities of ancestral and tip species, and the relative positions of two or more thresholds, from their joint posterior probability
Data from: Monte Carlo Strategies for selecting parameter values in simulation experiments
负责人:
关键词:
phylogenetic analysis;Simulation;Markov chain Monte Carlo;Plant domestication;Importance sampling
DOI:
doi:10.5061/dryad.366j4
摘要:
approaches can fare better in higher dimensions. We illustrate the framework with applications to phylogenetics and genetic archaeology.
Data from: Disentangling the formation of contrasting tree-line physiognomies combining model selection and Bayesian par
负责人:
关键词:
Plant;Demography;Ecology: population;Ecology: spatial;Dispersal;Pinus uncinata;Modeling: individual based;Temperate Forest;Methods: computer simulations
DOI:
doi:10.5061/dryad.8422
摘要:
l subset of processes required for tree-line formation. A Bayesian approach combined with Markov chain Monte Carlo methods was employed to obtai
Data from: Bayesian species delimitation can be robust to guide tree inference errors
负责人:
关键词:
species delimitation;guide tree;BPP;Simulation;MCMC
DOI:
doi:10.5061/dryad.m1r32
摘要:
in the reversible-jump Markov chain Monte Carlo (rjMCMC) algorithm (Green, 1995). It has been pointed out that the method tends to over-split if a random population
Data from: Cladogenetic and anagenetic models of chromosome number evolution: a Bayesian model averaging approach
负责人:
关键词:
anagenetic;Dysploidy;polyploidy;Bayes factors;ChromoSSE;phylogenetic models;whole genome duplication;chromosome evolution;reversible-jump Markov chain Monte Carlo;chromosome speciation;cladogenetic
DOI:
doi:10.5061/dryad.46m4b
摘要:
of ancestral chromosome numbers over molecular phylogenies and generated new interest in studying the role of chromosome changes in evolution. Howeve
Data from: State-and-transition simulation models: a framework for forecasting landscape change
负责人:
关键词:
Markov chain;Modeling;stochastic;land use change;spatial;ST-Sim;landscape dynamics;Holocene;landscape ecology
DOI:
doi:10.5061/dryad.g58k0
摘要:
interacting Markov chain in several important ways, including the ability to add discrete counters such as age and time-since-transition as state var
Data from: Implied weighting and its utility in palaeontological datasets: a study using modelled phylogenetic matrices
负责人:
关键词:
Cladistics;parsimony;character weights;phylogeny;Homoplasy
DOI:
doi:10.5061/dryad.7dq0j
摘要:
s of implied weighting on modelled phylogenetic data. We generated 100 character matrices consisting of 55 characters each using a Markov Chain morphology model

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