
Stable Non-Gaussian Random Processes
Stochastic Models with Infinite Variance
Chapman & Hall/CRC (Publisher)
1st Edition
Published on 1. June 1994
Book
Hardback
654 pages
978-0-412-05171-5 (ISBN)
Description
This book presents similarity between Gaussian and non-Gaussian stable multivariate distributions and introduces the one-dimensional stable random variables. It discusses the most basic sample path properties of stable processes, namely sample boundedness and continuity.
Reviews / Votes
"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
More details
Series
Language
English
Place of publication
Oxford
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Product notice
Laminated cover
Dimensions
Height: 242 mm
Width: 167 mm
Thickness: 40 mm
Weight
1055 gr
ISBN-13
978-0-412-05171-5 (9780412051715)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Gennady Samoradnitsky | M.S. Taqqu
Stable Non-Gaussian Random Processes
Stochastic Models with Infinite Variance
E-Book
11/2017
Chapman & Hall/CRC
€264.99
Available for download

Gennady Samoradnitsky | M.S. Taqqu
Stable Non-Gaussian Random Processes
Stochastic Models with Infinite Variance
E-Book
11/2017
Chapman & Hall/CRC
€264.99
Available for download
Persons
Samoradnitsky, Gennady
Author
Cornell University, New York, USA
Boston University, Massachusetts, USA
Content
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