Bayesian nonparametric data analysis [electronic resource] / Peter Müller, Fernando Andrés Quintana, Alejandro Jara, Tim Hanson.
Müller, Peter, author.; Quintana, Fernando Andrés, author.; Jara, Alejandro, author.; Hanson, Tim, author.
2015
QA279.5
Available Online

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Title Bayesian nonparametric data analysis [electronic resource] / Peter Müller, Fernando Andrés Quintana, Alejandro Jara, Tim Hanson.
Author Müller, Peter, author.
ISBN 9783319189680 electronic book
3319189689 electronic book
9783319189673
Published Cham, Switzerland : Springer, [2015]
Language English
Description 1 online resource.
Call Number QA279.5
Dewey Decimal Classification 519.542
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 on-line software pages.
Access Note Access limited to authorized users.
Added Author Quintana, Fernando Andrés, author.
Jara, Alejandro, author.
Hanson, Tim, author.
Series Springer series in statistics.
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Record Appears in Online Resources > Ebooks
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Preface
Acronyms
1.Introduction
2.Density Estimation
DP Models
3.Density Estimation
Models Beyond the DP
4.Regression
5.Categorical Data
6.Survival Analysis
7.Hierarchical Models
8.Clustering and Feature Allocation
9.Other Inference Problems and Conclusions
Appendix: DP package.

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