Stable Non-Gaussian Random Processes

Stochastic Models with Infinite Variance
1. Auflage 1994
ISBN: 978-0-412-05171-5
Verlag: Taylor & Francis Ltd

Buch, Englisch, 654 Seiten, Format (B × H): 167 mm x 242 mm, Gewicht: 1055 g

Reihe: Stochastic Modeling Series

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.

Autoren/Hrsg.

Samoradnitsky, Gennady

Taqqu, M.S. (Boston University, Massachusetts, USA)

Taqqu, M.S.

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik
• Mathematik | Informatik Mathematik Stochastik Elementare Stochastik
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Mathematik | Informatik Mathematik Stochastik Stochastische Prozesse

Inhaltsverzeichnis

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

Über Autor(innen)

Samoradnitsky, Gennady