Gennady Samoradnitsky

Stable Non-Gaussian Random Processes (eBook, ePUB)

Stochastic Models with Infinite Variance

• Format: ePub

Produktbeschreibung

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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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 632
• Erscheinungstermin: 22. November 2017
• Englisch
• ISBN-13: 9781351414791
• Artikelnr.: 50917379

Autorenporträt

Samoradnitsky, Gennady

Inhaltsangabe

1. Stable random variables on the real line 2. Multivariate stable distributions 3. Stable random processes and stochastic integrals 4. Dependence Structures of Multivariate Stable Distributions 5. Non-linear regression 6. Complex stable stochastic integrals and harmonizable processes 7. Self-similar processes 8. Chentsov random fields 9. Introduction to sample path properties 10. Boundedness, continuity and oscillations 11. Measurability, integrability and absolute continuity 12. Boundedness and continuity via metric entropy 13. Integral representation 14. Historical notes and extensions

Rezensionen

"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