Modified Estimators in Semiparametric Regression Models with Right-censored Data PDF Download
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Languages : en
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Author: Maria Karlsson
Publisher:
ISBN: 9789173058919
Category :
Languages : en
Pages : 25
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Author: Jiuping Xu
Publisher: Springer Nature
ISBN: 9819750989
Category :
Languages : en
Pages : 1703
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Author: Sam Efromovich
Publisher: CRC Press
ISBN: 1351679848
Category : Mathematics
Languages : en
Pages : 448
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Book Description
This book presents a systematic and unified approach for modern nonparametric treatment of missing and modified data via examples of density and hazard rate estimation, nonparametric regression, filtering signals, and time series analysis. All basic types of missing at random and not at random, biasing, truncation, censoring, and measurement errors are discussed, and their treatment is explained. Ten chapters of the book cover basic cases of direct data, biased data, nondestructive and destructive missing, survival data modified by truncation and censoring, missing survival data, stationary and nonstationary time series and processes, and ill-posed modifications. The coverage is suitable for self-study or a one-semester course for graduate students with a prerequisite of a standard course in introductory probability. Exercises of various levels of difficulty will be helpful for the instructor and self-study. The book is primarily about practically important small samples. It explains when consistent estimation is possible, and why in some cases missing data should be ignored and why others must be considered. If missing or data modification makes consistent estimation impossible, then the author explains what type of action is needed to restore the lost information. The book contains more than a hundred figures with simulated data that explain virtually every setting, claim, and development. The companion R software package allows the reader to verify, reproduce and modify every simulation and used estimators. This makes the material fully transparent and allows one to study it interactively. Sam Efromovich is the Endowed Professor of Mathematical Sciences and the Head of the Actuarial Program at the University of Texas at Dallas. He is well known for his work on the theory and application of nonparametric curve estimation and is the author of Nonparametric Curve Estimation: Methods, Theory, and Applications. Professor Sam Efromovich is a Fellow of the Institute of Mathematical Statistics and the American Statistical Association.
Author: Lei Pang
Publisher:
ISBN:
Category :
Languages : en
Pages : 76
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Author: Pavel Čížek
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Category :
Languages : en
Pages :
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Author: Hui-Lin Lin
Publisher:
ISBN:
Category :
Languages : en
Pages : 378
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Author: Torben Martinussen
Publisher: Springer Science & Business Media
ISBN: 0387339604
Category : Medical
Languages : en
Pages : 471
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Book Description
This book studies and applies modern flexible regression models for survival data with a special focus on extensions of the Cox model and alternative models with the aim of describing time-varying effects of explanatory variables. Use of the suggested models and methods is illustrated on real data examples, using the R-package timereg developed by the authors, which is applied throughout the book with worked examples for the data sets.
Author: Madan L. Puri
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110942003
Category : Mathematics
Languages : en
Pages : 456
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Book Description
No detailed description available for "Asymptotics in Statistics and Probability".
Author: Jianguo Sun
Publisher: Springer
ISBN: 0387371192
Category : Mathematics
Languages : en
Pages : 310
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Book Description
This book collects and unifies statistical models and methods that have been proposed for analyzing interval-censored failure time data. It provides the first comprehensive coverage of the topic of interval-censored data and complements the books on right-censored data. The focus of the book is on nonparametric and semiparametric inferences, but it also describes parametric and imputation approaches. This book provides an up-to-date reference for people who are conducting research on the analysis of interval-censored failure time data as well as for those who need to analyze interval-censored data to answer substantive questions.
