Title: Understanding computational Bayesian statistics
Description: Introduction to Bayesian statistics -- Monte Carlo sampling from the posterior -- Bayesian inference -- Bayesian statistics using conjugate priors -- Markov chains -- Markov chain Monte Carlo sampling from the posterior -- Statistical inference from a Markov chain Monte Carlo sample -- Logistic regression -- Poisson regression and proportional hazards model -- Gibbs sampling and hierarchical models -- Going forward with Markov chain Monte Carlo -- Appendix A: Using the included Minitab macros -- Appendix B: Using the included R functions.
Subjects: Bayesian statistical decision theory, Data processing, Bayes-Entscheidungstheorie, Methode van Bayes, Computational statistics