On the Estimation of Multiple Random Integrals and U-Statistics: 2079 (Lecture Notes in Mathematics)
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On the Estimation of Multiple Random Integrals and U-Statistics: 20...
Book Details
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Author: Péter Major
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Publisher: Springer
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Edition: 2013
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Binding: Paperback
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ISBN: 9783642376160
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Pages: 288
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Cover: Paperback
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Dimensions: 9.2 x 6.0 x 0.7 inches
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Languages: English
About The Book
This work explores limit theorems in probability theory where classical methods fail to provide effective solutions. By employing a linearization technique, the book simplifies complex problems and ensures that any resulting error from linearization is negligible. This error estimation leads to key large deviation-type problems, which form the core subject of the book.
The primary focus is on providing sharp estimates of the tail distributions for multiple integrals with respect to normalized empirical measures and degenerate U-statistics. Additionally, it addresses the supremum of appropriate classes of such quantities. To accomplish this, the book applies modern probability techniques, enabling an in-depth analysis of non-linear functionals of independent random variables.
The work is aimed at readers looking for new approaches and tools for proving limit theorems in situations where traditional methods are ineffective. It's a valuable resource for those in advanced probability theory, providing insights and methodologies for tackling challenging problems in this field.
