Bayesian Nonparametric Data Analysis

Label

Bayesian Nonparametric Data Analysis

Creator

• Mueller, Peter

Contributor

• Quintana, Fernando Andrés
• Jara, Alejandro
• Hanson, Tim

Subject

• Mathematics
• Mathematics, Applied
• Bayesian statistical decision theory
• Evolutionary computation

Language

eng

Summary

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

Member of

• Springer Series in Statistics Ser

Cataloging source

MiAaPQ

Literary form

non fiction

Nature of contents

dictionaries

Series statement

Springer Series in Statistics Ser