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Analysis of Doubly Truncated Data

An Introduction

Specificaties
Paperback, blz. | Engels
Springer Nature Singapore | e druk, 2019
ISBN13: 9789811362408
Rubricering
Springer Nature Singapore e druk, 2019 9789811362408
Onderdeel van serie SpringerBriefs in Statistics
Verwachte levertijd ongeveer 9 werkdagen

Samenvatting

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.

Specificaties

ISBN13:9789811362408
Taal:Engels
Bindwijze:paperback
Uitgever:Springer Nature Singapore

Inhoudsopgave

<p>Chapter 1: Introduction to double-truncation.- Chapter 2: Parametric inference under special exponential family.-&nbsp;Chapter 3: Parametric inference under location-scale family.-&nbsp;Chapter 4: Bayes inference.-&nbsp;Chapter 5: Nonparametric inference.-&nbsp;Chapter 6: Linear regression.-&nbsp;Appendix A: Data (if German company data are available).-&nbsp;Appendix B: R codes for inference under exponential family.-&nbsp;Appendix C: R codes for inference under location-scale family.-&nbsp;Appendix D: R codes for Bayes inference.-&nbsp;Appendix E: R codes for linear regression.</p>

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        Analysis of Doubly Truncated Data