Decision-Theoretic Foundations.- From Prior Information to Prior Distributions.- Bayesian Point Estimation.- Tests and Confidence Regions.- Bayesian Calculations.- Model Choice.- Admissibility and Complete Classes.- Invariance, Haar Measures, and Equivariant Estimators.- Hierarchical and Empirical Bayes Extensions.- A Defense of the Bayesian Choice.
This is an introduction to Bayesian statistics and decision theory, including advanced topics such as Monte Carlo methods. This new edition contains several revised chapters and a new chapter on model choice.
・計算機統計学・ベイズ統計学周辺でのお勧めの教科書10冊[2021-01-21に投稿]