Del i serien SpringerBriefs in Statistics

Analysis of Doubly Truncated Data

An Introduction

Häftad, Engelska, 2019

709 kr

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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.

Produktinformation

Utgivningsdatum2019-05-22
Mått155 x 235 x 8 mm
Vikt207 g
FormatHäftad
SpråkEngelska
SerieSpringerBriefs in Statistics
Antal sidor109
FörlagSpringer Verlag, Singapore
ISBN9789811362408

Tillhör följande kategorier

Matematisk statistik inom Naturvetenskap och teknik
Biovetenskap inom Naturvetenskap och teknik
Affärsapplikationer inom Data och IT

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.