Analysis of Doubly Truncated Data

An Introduction
1. Auflage 2019
ISBN: 978-981-1362-40-8
Verlag: Springer Nature Singapore

Buch, Englisch, 109 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 207 g

Reihe: Springer briefs in statistics

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.

Zielgruppe

Research

Autoren/Hrsg.

Emura, Takeshi

Dörre, Achim

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen
• Naturwissenschaften Biowissenschaften Angewandte Biologie Biomathematik
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik

Inhaltsverzeichnis

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.

Über Autor(innen)

Achim Dörre, University of Rostock



Takeshi Emura, Chang Gung University