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Book Categories |
Contributors | ||
1 | Introducing Markov chain Monte Carlo | 1 |
2 | Hepatitis B: a case study in MCMC methods | 21 |
3 | Markov chain concepts related to sampling algorithms | 45 |
4 | Introduction to general state-space Markov chain theory | 59 |
5 | Full conditional distributions | 75 |
6 | Strategies for improving MCMC | 89 |
7 | Implementing MCMC | 115 |
8 | Inference and monitoring convergence | 131 |
9 | Model determination using sampling-based methods | 145 |
10 | Hypothesis testing and model selection | 163 |
11 | Model checking and model improvement | 189 |
12 | Stochastic search variable selection | 203 |
13 | Bayesian model comparison via jump diffusions | 215 |
14 | Estimation and optimization of functions | 241 |
15 | Stochastic EM: method and application | 259 |
16 | Generalized linear mixed models | 275 |
17 | Hierarchical longitudinal modelling | 303 |
18 | Medical monitoring | 321 |
19 | MCMC for nonlinear hierarchical models | 339 |
20 | Bayesian mapping of disease | 359 |
21 | MCMC in image analysis | 381 |
22 | Measurement error | 401 |
23 | Gibbs sampling methods in genetics | 419 |
24 | Mixtures of distributions: inference and estimation | 441 |
25 | An archaeological example: radiocarbon dating | 465 |
Index | 481 |
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