Abstract
Achieving good mixing in Markov Chain Monte Carlo (MCMC) Bayesian phylogenetic analyses is essential to obtain valid posterior probabilities. Convergence of the runs to the region of the maximum a posteriori tree is not a sufficient requirement. Indeed, if the solution space is complex, other regions of the solution space might have non-negligible posterior probabilities. The Markov chains must therefore be able to leave the maximum a posteriori region in order to visit the other regions according to their posterior probabilities. Failure to sample a large enough proportion of the solution space may lead to overestimated posterior probabilities. Bolder topology moves
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