Analysis of doubly truncated data : an introduction
著者
書誌事項
Analysis of doubly truncated data : an introduction
（Springer Briefs in statistics, . JSS research series in statistics / editors-in-chief,
Springer, c2019
- : pbk
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注記
"This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd."--T.p. verso
Includes bibliographical references and index
ISSN for subseries: 2364-0057
内容説明・目次
内容説明
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.
目次
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.
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