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Bayesian Nonparametric Data Analysis

Specificaties
Paperback, blz. | Engels
Springer International Publishing | e druk, 2016
ISBN13: 9783319368429
Rubricering
Springer International Publishing e druk, 2016 9783319368429
Onderdeel van serie Springer Series in Statistics
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

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.

Specificaties

ISBN13:9783319368429
Taal:Engels
Bindwijze:paperback
Uitgever:Springer International Publishing

Inhoudsopgave

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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