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Stable Non-Gaussian Random Processes: Stochastic Models with Infinite Variance (Stochastic Modeling)
 
 
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Stable Non-Gaussian Random Processes: Stochastic Models with Infinite Variance (Stochastic Modeling) [Hardcover]

Gennady Samoradnitsky , M.S. Taqqu , Shaler Stidham Jr. , Marco Scarsini , Moshe Shaked

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"There has been a pressing need for a book on this subject...The authors have succeeded in filling the gap...I am very glad a standard reference about stable processes now exists." - Bulletin of the London Mathematical Society

Product Description

This book serves as a standard reference, making this area accessible not only to researchers in probability and statistics, but also to graduate students and practitioners. The book assumes only a first-year graduate course in probability. Each chapter begins with a brief overview and concludes with a wide range of exercises at varying levels of difficulty. The authors supply detailed hints for the more challenging problems, and cover many advances made in recent years.

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This chapter concerns univariate stable distributions. Read the first page
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