Nonparametric Estimation under Shape Constraints

Estimators, Algorithms and Asymptotics

Nonfiction, Science & Nature, Mathematics, Statistics, Business & Finance
Cover of the book Nonparametric Estimation under Shape Constraints by Piet Groeneboom, Geurt Jongbloed, Cambridge University Press
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Author: Piet Groeneboom, Geurt Jongbloed ISBN: 9781316188613
Publisher: Cambridge University Press Publication: December 11, 2014
Imprint: Cambridge University Press Language: English
Author: Piet Groeneboom, Geurt Jongbloed
ISBN: 9781316188613
Publisher: Cambridge University Press
Publication: December 11, 2014
Imprint: Cambridge University Press
Language: English

This book treats the latest developments in the theory of order-restricted inference, with special attention to nonparametric methods and algorithmic aspects. Among the topics treated are current status and interval censoring models, competing risk models, and deconvolution. Methods of order restricted inference are used in computing maximum likelihood estimators and developing distribution theory for inverse problems of this type. The authors have been active in developing these tools and present the state of the art and the open problems in the field. The earlier chapters provide an introduction to the subject, while the later chapters are written with graduate students and researchers in mathematical statistics in mind. Each chapter ends with a set of exercises of varying difficulty. The theory is illustrated with the analysis of real-life data, which are mostly medical in nature.

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This book treats the latest developments in the theory of order-restricted inference, with special attention to nonparametric methods and algorithmic aspects. Among the topics treated are current status and interval censoring models, competing risk models, and deconvolution. Methods of order restricted inference are used in computing maximum likelihood estimators and developing distribution theory for inverse problems of this type. The authors have been active in developing these tools and present the state of the art and the open problems in the field. The earlier chapters provide an introduction to the subject, while the later chapters are written with graduate students and researchers in mathematical statistics in mind. Each chapter ends with a set of exercises of varying difficulty. The theory is illustrated with the analysis of real-life data, which are mostly medical in nature.

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