Introduction to Nonparametric Estimation (Springer Series in Statistics)
Language: English
Published by Springer, 2010
- Softcover
- New
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- Title
- Introduction to Nonparametric Estimation (Springer Series in Statistics)
- Author
- Tsybakov, Alexandre B.
- Publisher
- Springer
- Publication year
- 2010
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 1441927093
- ISBN 13
- 9781441927095
- Series
- Book 104 of 160: Springer Series in Statistics
This book will be a valuable reference for researchers in the eare of nonparametrics.
"Synopsis" may belong to another edition of this title.
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.
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.
"About the title" may belong to another edition of this title.
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