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Nonparametric Estimation under Shape Constraints: Estimators, Algorithms and Asymptotics: 38 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 38) - Hardcover
Book 27 of 46: Cambridge Series in Statistical and Probabilistic Mathematics
Synopsis
This book introduces basic concepts of shape constrained inference and guides the reader to current developments in the subject.
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About the Authors
Piet Groeneboom is Professor Emeritus of Statistics at Delft University of Technology, The Netherlands.
Geurt Jongbloed is Professor of Statistics at Delft University of Technology, The Netherlands.
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Nonparametric Estimation under Shape Constraints: Estimators, Algorithms and Asymptotics
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Hardback. Condition: New. 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. Seller Inventory # 0075680
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Nonparametric Estimation Under Shape Constraints : Estimators, Algorithms and Asymptotics
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Nonparametric Estimation under Shape Constraints: Estimators, Algorithms and Asymptotics (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 38)
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Nonparametric Estimation under Shape Constraints: Estimators, Algorithms and Asymptotics (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 38)
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Nonparametric Estimation Under Shape Constraints: Estimators, Algorithms and Asymptotics
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Nonparametric Estimation Under Shape Constraints : Estimators, Algorithms and Asymptotics
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Nonparametric Estimation under Shape Constraints: Estimators, Algorithms and Asymptotics: 38 (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 38)
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ISBN 10: 0521864011
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Condition: New. This book introduces basic concepts of shape constrained inference and guides the reader to current developments in the subject. Series: Cambridge Series in Statistical and Probabilistic Mathematics. Num Pages: 428 pages, 90 b/w illus. 20 tables 190 exercises. BIC Classification: PBT. Category: (U) Tertiary Education (US: College). Dimension: 261 x 177 x 25. Weight in Grams: 942. . 2014. Illustrated. hardcover. . . . . Seller Inventory # V9780521864015
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Nonparametric Estimation under Shape Constraints:.
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Nonparametric Estimation under Shape Constraints (Hardcover)
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Hardcover. Condition: new. Hardcover. 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. This book treats the latest developments in the theory of order-restricted inference, with special attention to nonparametric methods and algorithmic aspects. 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780521864015
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