Nonparametric Bayesian Inference
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Fundamentals of Nonparametric Bayesian Inference
Author: Subhashis Ghosal
language: en
Publisher: Cambridge University Press
Release Date: 2017-06-26
Bayesian nonparametrics comes of age with this landmark text synthesizing theory, methodology and computation.
Bayesian Nonparametric Data Analysis
This book reviews nonparametric Bayesian methods and models that have proven useful in the context of data analysis. Rather than providing an encyclopedic review of probability models, the book’s structure follows a data analysis perspective. As such, the chapters are organized by traditional data analysis problems. In selecting specific nonparametric models, simpler and more traditional models are favored over specialized ones. The discussed methods are illustrated with a wealth of examples, including applications ranging from stylized examples to case studies from recent literature. The book also includes an extensive discussion of computational methods and details on their implementation. R code for many examples is included in online software pages.
Bayesian Nonparametrics
Author: J.K. Ghosh
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-05-11
This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. It will also appeal to statisticians in general. The book is primarily aimed at graduate students and can be used as the text for a graduate course in Bayesian non-parametrics.