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Bayesian Nonparametric Data Analysis

Bayesian Nonparametric Data Analysis

Paperback

Series: Springer Statistics

Medical ReferenceApplicationsProbability & Statistics

ISBN10: 3319368427
ISBN13: 9783319368429
Publisher: Springer Nature
Published: Oct 15 2016
Pages: 193
Weight: 0.66
Height: 0.44 Width: 6.14 Depth: 9.21
Language: English
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.

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