Analysis of Doubly Truncated Data An Introduction /

• Main Authors: Dörre, Achim (Author, http://id.loc.gov/vocabulary/relators/aut), Emura, Takeshi (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Singapore : Springer Singapore : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: JSS Research Series in Statistics,
• Subjects: Statistics .; Biostatistics.; Statistical Theory and Methods.; Applied Statistics.; Statistics and Computing/Statistics Programs.

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 effective...

Table of Contents:

• 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.