Empirical Processes in M-Estimation
Language: English
Published by Cambridge University Press, 2009
Series: Book 29 of 64 - Cambridge Series in Statistical and Probabilistic Mathematics
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 83.45
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - The theory of empirical processes provides valuable tools for the development of asymptotic theory in (nonparametric) statistical models, and makes possible the unified treatment of a number of them. This book reveals the relation between the asymptotic behaviour of M-estimators and the complexity of parameter space. Virtually all results are proved using only elementary ideas developed within the book; there is minimal recourse to abstract theoretical results. To make the results concrete, a detailed treatment is presented for two important examples of M-estimation, namely maximum likelihood and least squares. The theory also covers estimation methods using penalties and sieves. Many illustrative examples are given, including the Grenander estimator, estimation of functions of bounded variation, smoothing splines, partially linear models, mixture models and image analysis. Graduate students and professionals in statistics as well as those with an interest in applications, to such areas as econometrics, medical statistics, etc., will welcome this treatment.…
Seller Inventory # 9780521123259
- Title
- Empirical Processes in M-Estimation
- Author
- Sara A. van de Geer
- Publisher
- Cambridge University Press
- Publication year
- 2009
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0521123259
- ISBN 13
- 9780521123259
- Item weight
- 569 grams
- Dimensions
- 254x178x17 mm
- Series
- Book 29 of 64: Cambridge Series in Statistical and Probabilistic Mathematics
"Synopsis" may belong to another edition of this title.
Review
'... this excellent book will be extremely useful for graduate students and researchers in the general area of nonparametric estimation. It is a welcome addition to the existing literature and certainly recommended.' Niew Archief voor Wiskunde
"About the title" may belong to another edition of this title.
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