Bayesian Nonparametric Data Analysis (Springer Series in Statistics)

by Peter Muller

0 ratings • 0 reviews • 0 shelved
Book cover for Bayesian Nonparametric Data Analysis

Bookhype may earn a small commission from qualifying purchases. Full disclosure.

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.

  • ISBN10 1973896958
  • ISBN13 9781973896951
  • Publish Date 26 July 2017 (first published 26 June 2015)
  • Publish Status Active
  • Imprint Createspace Independent Publishing Platform
  • Format Paperback (US Trade)
  • Pages 46
  • Language English