<電子ブック>
Analysis of Doubly Truncated Data : An Introduction / by Achim Dörre, Takeshi Emura
(JSS Research Series in Statistics. ISSN:23640065)
版 | 1st ed. 2019. |
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出版者 | (Singapore : Springer Nature Singapore : Imprint: Springer) |
出版年 | 2019 |
大きさ | XVI, 109 p. 38 illus., 10 illus. in color : online resource |
著者標目 | *Dörre, Achim author Emura, Takeshi author SpringerLink (Online service) |
件 名 | LCSH:Statistics LCSH:Biometry LCSH:Mathematical statistics—Data processing FREE:Statistical Theory and Methods FREE:Applied Statistics FREE:Biostatistics FREE:Statistics and Computing |
一般注記 | Chapter 1: Introduction to double-truncation -- Chapter 2: Parametric inference under special exponential family -- Chapter 3: Parametric inference under location-scale family -- Chapter 4: Bayes inference -- Chapter 5: Nonparametric inference -- Chapter 6: Linear regression -- Appendix A: Data (if German company data are available) -- Appendix B: R codes for inference under exponential family -- Appendix C: R codes for inference under location-scale family -- Appendix D: R codes for Bayes inference -- Appendix E: R codes for linear regression This book introduces readers to statistical methodologies used to analyze doubly truncated data. The first book exclusively dedicated to the topic, it provides likelihood-based methods, Bayesian methods, non-parametric methods, and linear regression methods. These procedures can be used to effectively analyze continuous data, especially survival data arising in biostatistics and economics. Because truncation is a phenomenon that is often encountered in non-experimental studies, the methods presented here can be applied to many branches of science. The book provides R codes for most of the statistical methods, to help readers analyze their data. Given its scope, the book is ideally suited as a textbook for students of statistics, mathematics, econometrics, and other fields HTTP:URL=https://doi.org/10.1007/978-981-13-6241-5 |
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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 | 9789811362415 |
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電子リソース |
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EB00199470 |
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