Analysis of Doubly Truncated Data: An Introduction (JSS Research Series in Statistics) - Tapa blanda

Dörre, Achim; Emura, Takeshi

 
9789811362408: Analysis of Doubly Truncated Data: An Introduction (JSS Research Series in Statistics)

Sinopsis

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.

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Acerca del autor

Achim Dörre, University of Rostock

 

Takeshi Emura, Chang Gung University


De la contraportada

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.

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Otras ediciones populares con el mismo título

9789811362422: Analysis of Doubly Truncated Data: An Introduction

Edición Destacada

ISBN 10:  9811362424 ISBN 13:  9789811362422
Editorial: Springer, 2019
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