Bayesian phylogenetic inference aims to estimate the evolutionary relationships among
different lineages (species, populations, gene families, viral strains, etc.) in a model‐based …

Programs for Bayesian inference of phylogeny currently implement a unique and fixed suite
of models. Consequently, users of these software packages are simultaneously forced to …

Tests of absolute model fit are crucial in model-based inference because poorly structured
models can lead to biased parameter estimates. In Bayesian inference, posterior predictive …

Bayesian inference is becoming a common statistical approach to phylogenetic estimation
because, among other reasons, it allows for rapid analysis of large data sets with complex …

Phylogenies are central to many research areas in biology and commonly estimated using
likelihood based methods. Unfortunately, any likelihood based method, including Bayesian …

Researchers studying the evolution of viral pathogens and other organisms increasingly
encounter and use large and complex data sets from multiple different sources. Statistical …

Abstract Background Recent developments in Bayesian phylogenetic models have
increased the range of inferences that can be drawn from molecular sequence data …

The ideal approach to Bayesian phylogenetic inference is to estimate all parameters of
interest jointly in a single hierarchical model. However, this is often not feasible in practice …

Bayesian methods have become very popular in molecular phylogenetics due to the
availability of user-friendly software for running sophisticated models of evolution. However …

Bayesian phylogenetics is now facing a critical point. Over the last 20 years, Bayesian
methods have reshaped phylogenetic inference and gained widespread popularity due to …