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[null,"1.","Record Nr.",null,"UNINA9910350247703321"]
[null,null,"Autore",null,"Dörre Achim"]
[null,null,"Titolo",null,"Analysis of Doubly Truncated Data : An Introduction / / by Achim Dörre, Takeshi Emura"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2019"]
[null,null,"ISBN",null,"981-13-6241-6"]
[null,null,"Edizione",null,"[1st ed. 2019.]"]
[null,null,"Descrizione fisica",null,"1 online resource (XVI, 109 p. 38 illus., 10 illus. in color.)"]
[null,null,"Collana",null,"JSS Research Series in Statistics, , 2364-0065"]
[null,null,"Disciplina",null,"519.5"]
[null,null,"Soggetti",null,"Statistics"]
[{"$nulls":4},"Biometry"]
[{"$nulls":4},"Mathematical statistics - Data processing"]
[{"$nulls":4},"Statistical Theory and Methods"]
[{"$nulls":4},"Applied Statistics"]
[{"$nulls":4},"Biostatistics"]
[{"$nulls":4},"Statistics and Computing"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"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."]
[null,null,null,"Sommario/riassunto","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."]