Practical Nonparametric and Semiparametric Bayesian Statistics [Paperback]

A compilation of original articles by Bayesian experts, this volume presents perspectives on recent developments on nonparametric and semiparametric methods in Bayesian statistics. The articles discuss how to conceptualize and develop Bayesian models using rich classes of nonparametric and semiparametric methods, how to use modern computational tools to summarize inferences, and how to apply these methodologies through the analysis of case studies.A compilation of original articles by Bayesian experts, this volume presents perspectives on recent developments on nonparametric and semiparametric methods in Bayesian statistics. The articles discuss how to conceptualize and develop Bayesian models using rich classes of nonparametric and semiparametric methods, how to use modern computational tools to summarize inferences, and how to apply these methodologies through the analysis of case studies.I Dirichlet and Related Processes.- 1 Computing Nonparametric Hierarchical Models.- 1.1 Introduction.- 1.2 Notation and Perspectives.- 1.3 Posterior Sampling in Dirichlet Process Mixtures.- 1.4 An Example with Poisson-Gamma Structure.- 1.5 An Example with Normal Structure.- 2 Computational Methods for Mixture of Dirichlet Process Models.- 2.1 Introduction.- 2.2 The Basic Algorithm.- 2.3 More Efficient Algorithms.- 2.4 Non-Conjugate Models.- 2.5 Discussion.- 3 Nonparametric Bayes Methods Using Predictive Updating.- 3.1 Introduction.- 3.2 Onn=1.- 3.3 A Recursive Algorithm.- 3.4 Interval Censoring.- 3.5 Censoring Example.- 3.6 Mixing Example.- 3.7 Onn= 2.- 3.8 Concluding Remarks.- 4 Dynamic Display of Changing Posterior in Bayesian Survival Analysis.- 4.1 Introduction and Summary.- 4.2 A Gibbs Sampler for Censored Data.- 4.3 Proof of Proposition 1.- 4.4 Importance Sampling.- 4.5 The Environment for Dynamic Graphics.- 4.6 Appendix: Completion of the Proof of Proposition 1.- 5 Semiparametric Bayesian Methods for Random Effects Models.- 5.1 Introduction.- 5.2 Normal Linear Random Effecl“%