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On the Estimation of Multiple Random Integrals and U-Statistics: 2079 (Lecture Notes in Mathematics) - Tapa blanda
Sinopsis
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.
"Sinopsis" puede pertenecer a otra edición de este libro.
De la contraportada
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.
"Sobre este título" puede pertenecer a otra edición de este libro.
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On the Estimation of Multiple Random Integrals and U-Statistics
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On the Estimation of Multiple Random Integrals and U-Statistics
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Condición: New. pp. 306. Nº de ref. del artículo: 2651413496
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On the Estimation of Multiple Random Integrals and U-Statistics (Lecture Notes in Mathematics, 2079)
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On the Estimation of Multiple Random Integrals and U-Statistics
Librería: Biblios, Frankfurt am main, HESSE, Alemania
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Condición: New. pp. 306. Nº de ref. del artículo: 1851413490
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On the Estimation of Multiple Random Integrals and U-Statistics
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Springer Berlin Heidelberg Jul 2013, 2013
ISBN 10: 3642376169
ISBN 13: 9783642376160
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 304 pp. Englisch. Nº de ref. del artículo: 9783642376160
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On the Estimation of Multiple Random Integrals and U-Statistics
Publicado por
Springer Berlin Heidelberg, 2013
ISBN 10: 3642376169
ISBN 13: 9783642376160
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. 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. Nº de ref. del artículo: 9783642376160
Cantidad disponible: 1 disponibles
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On the Estimation of Multiple Random Integrals and U-Statistics (Lecture Notes in Mathematics, 2079)
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On the Estimation of Multiple Random Integrals and U-Statistics
Publicado por
Springer Berlin Heidelberg, 2013
ISBN 10: 3642376169
ISBN 13: 9783642376160
Nuevo
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Librería: moluna, Greven, Alemania
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Includes supplementary material: sn.pub/extrasThis 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 t. Nº de ref. del artículo: 5058682
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On the Estimation of Multiple Random Integrals and U-Statistics
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On the Estimation of Multiple Random Integrals and U-Statistics
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