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Analysis of doubly truncated data = ...
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Dorre, Achim.
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Analysis of doubly truncated data = an introduction /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Analysis of doubly truncated data/ by Achim Dorre, Takeshi Emura.
其他題名:
an introduction /
作者:
Dorre, Achim.
其他作者:
Emura, Takeshi.
出版者:
Singapore :Springer Singapore : : 2019.,
面頁冊數:
xvi, 109 p. :ill., digital ;24 cm.
內容註:
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.
Contained By:
Springer eBooks
標題:
Mathematical statistics. -
電子資源:
https://doi.org/10.1007/978-981-13-6241-5
ISBN:
9789811362415
Analysis of doubly truncated data = an introduction /
Dorre, Achim.
Analysis of doubly truncated data
an 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
Standard No.: 10.1007/978-981-13-6241-5doiSubjects--Topical Terms:
516858
Mathematical statistics.
LC Class. No.: QA276 / .D865 2019
Dewey Class. No.: 519.5
Analysis of doubly truncated data = an introduction /
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