Data from: Deflating trees: improving Bayesian branch-length estimates using informed priors

Bradley J. Nelson, John J. Andersen & Jeremy M. Brown
Prior distributions can have a strong effect on the results of Bayesian analyses. However, no general consensus exists for how priors should be set in all circumstances. Branch-length priors are of particular interest for phylogenetics, because they affect many parameters and biologically relevant inferences have been shown to be sensitive to the chosen prior distribution. Here, we explore the use of outside information to set informed branch-length priors and compare inferences from these informed analyses...
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