Subhashis Ghosal (North Carolina State University), Aad van der Vaart (Universiteit Leiden)

Gebundenes Buch

Fundamentals of Nonparametric Bayesian Inference

Beschreibung

Written by top researchers, this self-contained text is the authoritative account of Bayesian nonparametrics, a nearly universal framework for inference in statistics and machine learning, with practical use in all areas of science, including economics and biostatistics. Appendices with prerequisites and numerous exercises support its use for graduate courses.

Autor

Subhashis Ghosal is Professor of Statistics at North Carolina State University. His primary research interest is in the theory, methodology and various applications of Bayesian nonparametrics. He has edited one book, written nearly one hundred papers, and serves on the editorial boards of the Annals of Statistics, Bernoulli, and the Electronic Journal of Statistics. He is an elected fellow of the Institute of Mathematical Statistics, the American Statistical Association and the International Society for Bayesian Analysis.

Produktdetails

• Cambridge Series in Statistical and Probabilistic Mathematics
• Verlag: Cambridge University Press
• Seitenzahl: 672
• Erscheinungstermin: 19. März 2019
• Englisch
• Abmessung: 260mm x 183mm x 40mm
• Gewicht: 1370g
• ISBN-13: 9780521878265
• ISBN-10: 0521878268
• Artikelnr.: 47350216