On the Estimation of Multiple Random Integrals and U-Statistics
Language: English
Published by Springer, 2013
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 45.70
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - This work starts with the study of those limit theorems in probability theory for which classical methods do not work. In many cases some form of linearization can help to solve the problem, because the linearized version is simpler. But in order to apply such a method we have to show that the linearization causes a negligible error. The estimation of this error leads to some important large deviation type problems, and the main subject of this work is their investigation. We provide sharp estimates of the tail distribution of multiple integrals with respect to a normalized empirical measure and so-called degenerate U-statistics and also of the supremum of appropriate classes of such quantities. The proofs apply a number of useful techniques of modern probability that enable us to investigate the non-linear functionals of independent random variables.This lecture note yields insights into these methods, and may also be useful for those who only want some new tools to help them prove limit theorems when standard methods are not a viable option.…
Seller Inventory # 9783642376160
- Title
- On the Estimation of Multiple Random Integrals and U-Statistics
- Author
- Péter Major
- Publisher
- Springer
- Publication year
- 2013
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3642376169
- ISBN 13
- 9783642376160
- Item weight
- 464 grams
- Dimensions
- 235x155x17 mm
This lecture note yields insights into these methods, and may also be useful for those who only want some new tools to help them prove limit theorems when standard methods are not a viable option.
"Synopsis" may belong to another edition of this title.
From the Back Cover
This lecture note yields insights into these methods, and may also be useful for those who only want some new tools to help them prove limit theorems when standard methods are not a viable option.
"About the title" may belong to another edition of this title.
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