<電子ブック>
Bayesian Nonparametric Data Analysis / by Peter Müller, Fernando Andres Quintana, Alejandro Jara, Tim Hanson
(Springer Series in Statistics. ISSN:2197568X)
版 | 1st ed. 2015. |
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出版者 | (Cham : Springer International Publishing : Imprint: Springer) |
出版年 | 2015 |
本文言語 | 英語 |
大きさ | XIV, 193 p. 59 illus., 10 illus. in color : online resource |
著者標目 | *Müller, Peter author Quintana, Fernando Andres author Jara, Alejandro author Hanson, Tim author SpringerLink (Online service) |
件 名 | LCSH:Statistics LCSH:Mathematical statistics -- Data processing 全ての件名で検索 LCSH:Biometry FREE:Statistical Theory and Methods FREE:Statistics and Computing FREE:Biostatistics |
一般注記 | 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 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 HTTP:URL=https://doi.org/10.1007/978-3-319-18968-0 |
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電子ブック | 配架場所 | 資料種別 | 巻 次 | 請求記号 | 状 態 | 予約 | コメント | ISBN | 刷 年 | 利用注記 | 指定図書 | 登録番号 |
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電子ブック | オンライン | 電子ブック |
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Springer eBooks | 9783319189680 |
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電子リソース |
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EB00229608 |
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