Analysis of Doubly Truncated Data: An Introduction: SpringerBriefs in Statistics
Autor Achim Dörre, Takeshi Emuraen Limba Engleză Paperback – 22 mai 2019
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Specificații
ISBN-13: 9789811362408
ISBN-10: 9811362408
Pagini: 115
Ilustrații: XVI, 109 p. 38 illus., 10 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.19 kg
Ediția:1st ed. 2019
Editura: Springer Nature Singapore
Colecția Springer
Seriile SpringerBriefs in Statistics, JSS Research Series in Statistics
Locul publicării:Singapore, Singapore
ISBN-10: 9811362408
Pagini: 115
Ilustrații: XVI, 109 p. 38 illus., 10 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.19 kg
Ediția:1st ed. 2019
Editura: Springer Nature Singapore
Colecția Springer
Seriile SpringerBriefs in Statistics, JSS Research Series in Statistics
Locul publicării:Singapore, Singapore
Cuprins
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.
Recenzii
“The aim of this book is to provide some fundamental ideas and methodologies for analysing doubly truncated data. ... The methodology of this book could be helpful to avoid a systematic bias in the contents of data due to loss of information.” (Nikita E. Ratanov, zbMATH 1434.62008, 2020)
Notă biografică
Achim Dörre, University of Rostock
Takeshi Emura, Chang Gung University
Takeshi Emura, Chang Gung University
Textul de pe ultima copertă
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.
Caracteristici
Serves as an accessible introductory textbook on the analysis of doubly truncated data for students of statistics, mathematics, and econometrics Provides illustrative examples from biostatistics, economics, and other fields, with R codes to help readers analyze their data Presents clearer and more detailed explanations than those found in most journal papers