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Bayesian Nonparametric Data Analysis (Paperback)

by Peter Müller

Springer

Paperback or Softback 193 pages Oct 15, 2016

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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.
Author:
Peter Müller
Publisher:
Springer
Publication Date:
Oct 15, 2016
Number of pages:
193 pages
Binding:
Paperback or Softback
ISBN-10:
3319368427
ISBN-13:
9783319368429