Contents
List of exercises ix
Preface to the series xv
Preface xix
1 The subjective interpretation of probability 1
2 Bayesian inference 11
3 Point estimation 29
4 Frequentist properties of Bayesian estimators 37
5 Interval estimation 51
6 Hypothesis testing 59
7 Prediction 71
8 Choiceofprior 79
9 Asymptotic Bayes 91
10 The linear regression model 107
11 Basics of Bayesian computation 117
11.1 Monte Carlo integration 119
11.2 Importance sampling 124
11.3 Gibbs sampling and the Metropolis–Hastings algorithm 128
11.4 Other (noniterative) methods for generating random variates 157
12 Hierarchical models 169
13 The linear regression model with general covariance matrix 191
14 Latent variable models 203
15 Mixture models 253
15.1 Some scale mixture of normals models 254
15.2 Other continuous and finite-mixture models 260
16 Bayesian model averaging and selection 281
16.1 Bayesian model averaging 282
16.2 Bayesian variable selection and marginal likelihood calculation 287
17 Some stationary time series models 297
18 Some nonstationary time series models 319
Appendix 335
Bibliography 343
Index 353