Stable non-Gaussian random processes : stochastic models with infinite variance
Author(s)
Bibliographic Information
Stable non-Gaussian random processes : stochastic models with infinite variance
（Stochastic modeling）
Chapman & Hall/CRC, 2000
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Note
Originally published: New York ; London : Chapman & Hall, c1994
Bibliography: p. [603]-619
Includes indexes
Description and Table of Contents
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.
Table of Contents
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
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