Bayesian Nonparametric Data Analysis

  • Peter Müller
  • Fernando Andres Quintana
  • Alejandro Jara
  • Tim Hanson

Part of the Springer Series in Statistics book series (SSS)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Peter Müller, Fernando Andrés Quintana, Alejandro Jara, Tim Hanson
    Pages 1-5
  3. Peter Müller, Fernando Andrés Quintana, Alejandro Jara, Tim Hanson
    Pages 7-31
  4. Peter Müller, Fernando Andrés Quintana, Alejandro Jara, Tim Hanson
    Pages 33-50
  5. Peter Müller, Fernando Andrés Quintana, Alejandro Jara, Tim Hanson
    Pages 51-75
  6. Peter Müller, Fernando Andrés Quintana, Alejandro Jara, Tim Hanson
    Pages 77-100
  7. Peter Müller, Fernando Andrés Quintana, Alejandro Jara, Tim Hanson
    Pages 101-123
  8. Peter Müller, Fernando Andrés Quintana, Alejandro Jara, Tim Hanson
    Pages 125-143
  9. Peter Müller, Fernando Andrés Quintana, Alejandro Jara, Tim Hanson
    Pages 145-174
  10. Peter Müller, Fernando Andrés Quintana, Alejandro Jara, Tim Hanson
    Pages 175-178
  11. Back Matter
    Pages 179-193

About this book

Introduction

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 on-line software pages.

Keywords

Markov chains Monte Carlo bayesian statistics clustering mixture models nonparametrics

Authors and affiliations

  • Peter Müller
    • 1
  • Fernando Andres Quintana
    • 2
  • Alejandro Jara
    • 3
  • Tim Hanson
    • 4
  1. 1.Department of MathematicsUniversity of Texas at AustinAustinUSA
  2. 2.Departamento de EstadísticaPontificia Universidad CatólicaSantiagoChile
  3. 3.Departamento de EstadísticaPontificia Universidad CatólicaSantiagoChile
  4. 4.Department of StatisticsUniversity of South CarolinaColumbiaUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-18968-0
  • Copyright Information Springer International Publishing Switzerland 2015
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-18967-3
  • Online ISBN 978-3-319-18968-0
  • Series Print ISSN 0172-7397
  • Series Online ISSN 2197-568X
  • About this book
Industry Sectors
Pharma
Biotechnology
Electronics
Telecommunications
Aerospace
Oil, Gas & Geosciences