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Synopsis
Developed from lecture notes and ready to be used for a course on the graduate level, this concise text aims to introduce the fundamental concepts of nonparametric estimation theory while maintaining the exposition suitable for a first approach in the field.
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From the Back Cover
Methods of nonparametric estimation are located at the core of modern statistical science. The aim of this book is to give a short but mathematically self-contained introduction to the theory of nonparametric estimation. The emphasis is on the construction of optimal estimators; therefore the concepts of minimax optimality and adaptivity, as well as the oracle approach, occupy the central place in the book.
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“The book is meant to be an introduction to the rich theory of nonparametric estimation through some simple models and examples. The detailed proofs given in the book will help the interested reader to understand the subject better. This well written book will be welcomed by all those interested in learning the presented concepts. The author should be complimented for a good treatise with detailed proofs of...
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- PublisherSpringer
- Publication date2010
- ISBN 10 1441927093
- ISBN 13 9781441927095
- BindingPaperback
- LanguageEnglish
- Number of pages224
- Rating
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Introduction to Nonparametric Estimation
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Introduction to Nonparametric Estimation (Springer Series in Statistics)
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Introduction to Nonparametric Estimation
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Springer-Verlag New York Inc., 2010
ISBN 10: 1441927093
ISBN 13: 9781441927095
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Introduction to Nonparametric Estimation
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Springer New York, Springer US Nov 2010, 2010
ISBN 10: 1441927093
ISBN 13: 9781441927095
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Methods of nonparametric estimation are located at the core of modern statistical science. The aim of this book is to give a short but mathematically self-contained introduction to the theory of nonparametric estimation. The emphasis is on the construction of optimal estimators; therefore the concepts of minimax optimality and adaptivity, as well as the oracle approach, occupy the central place in the book.This is a concise text developed from lecture notes and ready to be used for a course on the graduate level. The main idea is to introduce the fundamental concepts of the theory while maintaining the exposition suitable for a first approach in the field. Therefore, the results are not always given in the most general form but rather under assumptions that lead to shorter or more elegant proofs.The book has three chapters. Chapter 1 presents basic nonparametric regression and density estimators and analyzes their properties. Chapter 2 is devoted to a detailed treatment of minimax lower bounds. Chapter 3 develops more advanced topics: Pinsker's theorem, oracle inequalities, Stein shrinkage, and sharp minimax adaptivity. 228 pp. Englisch. Seller Inventory # 9781441927095
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Introduction to Nonparametric Estimation
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Concise and self-contained treatment of the theoryThorough analysis of optimality and adaptivity issuesDetailed account on minimax lower boundsThis book will be a valuable reference for researchers in the eare of nonparametrics. Seller Inventory # 4173206
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Introduction to Nonparametric Estimation
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ISBN 10: 1441927093
ISBN 13: 9781441927095
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Methods of nonparametric estimation are located at the core of modern statistical science. The aim of this book is to give a short but mathematically self-contained introduction to the theory of nonparametric estimation. The emphasis is on the construction of optimal estimators; therefore the concepts of minimax optimality and adaptivity, as well as the oracle approach, occupy the central place in the book.This is a concise text developed from lecture notes and ready to be used for a course on the graduate level. The main idea is to introduce the fundamental concepts of the theory while maintaining the exposition suitable for a first approach in the field. Therefore, the results are not always given in the most general form but rather under assumptions that lead to shorter or more elegant proofs.The book has three chapters. Chapter 1 presents basic nonparametric regression and density estimators and analyzes their properties. Chapter 2 is devoted to a detailed treatment of minimax lower bounds. Chapter 3 develops more advanced topics: Pinsker's theorem, oracle inequalities, Stein shrinkage, and sharp minimax adaptivity. Seller Inventory # 9781441927095
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Introduction to Nonparametric Estimation
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