Computational Bayesian statistics: an introduction - 11

Meaningful use of advanced Bayesian methods requires a good understanding of the fundamentals.

This engaging book explains the ideas that underpin the construction and analysis of Bayesian models, with particular focus on computational methods and schemes.

The unique features of the text are the extensive discussion of available software packages combined with a brief but complete and mathematically rigorous introduction to Bayesian inference.

The text introduces Monte Carlo methods, Markov chain Monte Carlo methods, and Bayesian software, with additional material on model validation and comparison, transdimensional MCMC, and conditionally Gaussian models.