Bayesian Nonparametric Data Analysis (Paperback, Softcover reprint of the original 1st ed. 2015)

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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.

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Product Description

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.

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Product Details

General

Imprint

Springer International Publishing AG

Country of origin

Switzerland

Series

Springer Series in Statistics

Release date

October 2016

Availability

Expected to ship within 10 - 15 working days

First published

2015

Authors

, , ,

Dimensions

235 x 155 x 11mm (L x W x T)

Format

Paperback

Pages

193

Edition

Softcover reprint of the original 1st ed. 2015

ISBN-13

978-3-319-36842-9

Barcode

9783319368429

Categories

LSN

3-319-36842-7



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