Data from: Critically evaluating the theory and performance of Bayesian analyis of macroevolutionary mixtures
Moore, Brian R., University of California, Davis
Hoehna, Sebastian, University of California, Berkeley
May, Michael R., University of California, Davis
Rannala, Bruce, University of California, Davis
Huelsenbeck, John P., University of California, Berkeley
Published Aug 01, 2017 on Dryad.
Cite this dataset
Moore, Brian R. et al. (2017). Data from: Critically evaluating the theory and performance of Bayesian analyis of macroevolutionary mixtures [Dataset]. Dryad. https://doi.org/10.5061/dryad.mb0sd
Bayesian analysis of macroevolutionary mixtures (BAMM) has recently taken the study of lineage diversification by storm. BAMM estimates the diversification-rate parameters (speciation and extinction) for every branch of a study phylogeny and infers the number and location of diversification-rate shifts across branches of a tree. Our evaluation of BAMM reveals two major theoretical errors: (i) the likelihood function (which estimates the model parameters from the data) is incorrect, and (ii) the compound Poisson process prior model (which describes the prior distribution of diversification-rate shifts across branches) is incoherent. Using simulation, we demonstrate that these theoretical issues cause statistical pathologies; posterior estimates of the number of diversification-rate shifts are strongly influenced by the assumed prior, and estimates of diversification-rate parameters are unreliable. Moreover, the inability to correctly compute the likelihood or to correctly specify the prior for rate-variable trees precludes the use of Bayesian approaches for testing hypotheses regarding the number and location of diversification-rate shifts using BAMM.
This repo hosts modified BAMM code that we used in our project exploring theoretical issues and statistical problems with BAMM.