Hierarchical Models for Mitochondrial DNA Sequence Data

We introduce a Bayesian hierarchical model for mitochondrial DNA sequence data, which is fitted via acceptance-rejection algorithms. The model incorporates parametric models of population history explicitly as well as a mutational process allowing for a simultaneous parameter estimation whose importance has become increasingly clear in many recent studies. The model is applied to a sample of DNA sequences from the Italian population.