Fundamentals of Nonparametric Bayesian Inference

ISBN-13: 9780521878265 / Angielski / Twarda / 2017 / 670 str.

Subhashis Ghosal; Aad Van Der Vaart

Opis

Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation.

Recenzje

'This book can serve as a textbook for a graduate course on Bayesian nonparametrics. It can also be used as a reference book for researchers in both statistics and machine learning, as well as application areas such as econometrics and biostatistics.' Yuehua Wu, MathSciNet

Spis treści

Preface; Glossary of symbols; 1. Introduction; 2. Priors on function spaces; 3. Priors on spaces of probability measures; 4. Dirichlet processes; 5. Dirichlet process mixtures; 6. Consistency: general theory; 7. Consistency: examples; 8. Contraction rates: general theory; 9. Contraction rates: examples; 10. Adaptation and model selection; 11. Gaussian process priors; 12. Infinite-dimensional Bernstein–von Mises theorem; 13. Survival analysis; 14. Discrete random structures; Appendices; References; Author index; Subject index.