國立高雄大學圖資館 |

Language: English

Back

Analysis of doubly truncated dataan ...

Dorre, Achim.

Analysis of doubly truncated dataan introduction /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Analysis of doubly truncated databy Achim Dorre, Takeshi Emura.
Reminder of title:	an introduction /
Author:	Dorre, Achim.
other author:	Emura, Takeshi.
Published:	Singapore :Springer Singapore :2019.
Description:	xvi, 109 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Mathematical statistics.
Online resource:	https://doi.org/10.1007/978-981-13-6241-5
ISBN:	9789811362415$q(electronic bk.)

Analysis of doubly truncated dataan introduction /
Dorre, Achim.

Analysis of doubly truncated dataan introduction /[electronic resource] :by Achim Dorre, Takeshi Emura. - Singapore :Springer Singapore :2019. - xvi, 109 p. :ill., digital ;24 cm. - JSS research series in statistics,2364-0057. - JSS research series in statistics..

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.

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.

ISBN: 9789811362415$q(electronic bk.)

Standard No.: 10.1007/978-981-13-6241-5doiSubjects--Topical Terms:

181877
Mathematical statistics.

LC Class. No.: QA276 / .D865 2019

Dewey Class. No.: 519.5

Analysis of doubly truncated dataan introduction /
LDR:02377nmm a2200337 a 4500 001 559037
003 DE-He213
005 20191101115619.0
006 m d
007 cr nn 008maaau
008 191219s2019 si s 0 eng d
020 $a 9789811362415$q(electronic bk.)
020 $a 9789811362408$q(paper)
024 7 $a 10.1007/978-981-13-6241-5 $2 doi
035 $a 978-981-13-6241-5
040 $a GP $c GP
041 0 $a eng
050 4 $a QA276 $b .D865 2019
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.5 $2 23
090 $a QA276 $b .D716 2019
100 1 $a Dorre, Achim. $3 841910
245 1 0 $a Analysis of doubly truncated data $h [electronic resource] : $b an introduction / $c by Achim Dorre, Takeshi Emura.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2019.
300 $a xvi, 109 p. : $b ill., digital ; $c 24 cm.
490 1 $a JSS research series in statistics, $x 2364-0057
505 0 $a 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.
520 $a 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.
650 0 $a Mathematical statistics. $3 181877
650 1 4 $a Statistical Theory and Methods. $3 274054
650 2 4 $a Applied Statistics. $3 805583
650 2 4 $a Biostatistics. $3 339693
650 2 4 $a Statistics and Computing/Statistics Programs. $3 275710
700 1 $a Emura, Takeshi. $3 796751
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a JSS research series in statistics. $3 825939
856 4 0 $u https://doi.org/10.1007/978-981-13-6241-5
950 $a Mathematics and Statistics (Springer-11649)