Bayesian Nonparametric Data Analysis

Bayesian Nonparametric Data Analysis

EnglishPaperback / softbackPrint on demand
Müller, Peter
Springer, Berlin
EAN: 9783319368429
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Detailed information

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.

EAN 9783319368429
ISBN 3319368427
Binding Paperback / softback
Publisher Springer, Berlin
Publication date October 15, 2016
Pages 193
Language English
Dimensions 235 x 155
Country Switzerland
Readership Professional & Scholarly
Authors Hanson Tim; Jara Alejandro; Muller, Peter; Quintana Fernando Andres
Illustrations XIV, 193 p. 59 illus., 10 illus. in color.
Edition Softcover reprint of the original 1st ed. 2015
Series Springer Series in Statistics