Model selection and parameter inference in phylogenetics using Nested Sampling

Understand

Bayesian inference methods rely on numerical algorithms for both model selection and parameter inference.

• In general, these algorithms require a high computational effort to yield reliable estimates.
• One of the major challenges in phylogenetics is the estimation of the marginal likelihood.
• This quantity is commonly used for comparing different evolutionary models, but its calculation, even for simple models, incurs high computational cost.