Data from: An efficient independence sampler for updating branches in Bayesian Markov chain Monte Carlo sampling of phylogenetic trees

Andre J. Aberer, Alexandros Stamatakis & Fredrik Ronquist
Sampling tree space is the most challenging aspect of Bayesian phylogenetic inference. The sheer number of alternative topologies is problematic by itself. In addition, the complex dependency between branch lengths and topology increases the difficulty of moving efficiently among topologies. Current tree proposals are fast but sample new trees using primitive transformations or re-mappings of old branch lengths. This reduces acceptance rates and presumably slows down convergence and mixing. Here, we explore branch proposals that...
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