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Is BAMM flawed? Theoretical and practical concerns in the analysis of multi-rate diversification models

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DataONE2020-06-24 更新2025-04-19 收录
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BAMM (Bayesian Analysis of Macroevolutionary Mixtures) is a statistical framework that uses reversible jump MCMC to infer complex macroevolutionary dynamics of diversification and phenotypic evolution on phylogenetic trees. A recent article by Moore and coauthors (MEA) reported a number of theoretical and practical concerns with BAMM. Major claims from MEA are that (1) BAMM's likelihood function is incorrect, because it does not account for unobserved rate shifts; (2) the posterior distribution on the number of rate shifts is overly sensitive to the prior; and (3) diversification rate estimates from BAMM are unreliable. Here, we show that these and other conclusions from MEA are generally incorrect or unjustified. We first demonstrate that MEA's numerical assessment of the BAMM likelihood is compromised by their use of an invalid likelihood function. We then show that “unobserved rate shifts” appear to be irrelevant for biologically-plausible parameterizations of the diversification pro...

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2025-04-14
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