Stable non-Gaussian self-similar processes with stationary increments

✍ Scribed by Pipiras, Vladas; Taqqu, Murad S

• Publisher: Springer
• Year: 2017
• Tongue: English
• Leaves: 143
• Series: SpringerBriefs in probability and mathematical statistics
• Category: Library

✦ Synopsis

This book provides a self-contained presentation on the structure of a large class of stable processes, known as self-similar mixed moving averages. The authors present a way to describe and classify these processes by relating them to so-called deterministic flows. The first sections in the book review random variables, stochastic processes, and integrals, moving on to rigidity and flows, and finally ending with mixed moving averages and self-similarity. In-depth appendices are also included. This book is aimed at graduate students and researchers working in probability theory and statistics. Read more...

Abstract: This book provides a self-contained presentation on the structure of a large class of stable processes, known as self-similar mixed moving averages. The authors present a way to describe and classify these processes by relating them to so-called deterministic flows. The first sections in the book review random variables, stochastic processes, and integrals, moving on to rigidity and flows, and finally ending with mixed moving averages and self-similarity. In-depth appendices are also included. This book is aimed at graduate students and researchers working in probability theory and statistics

✦ Table of Contents

Front Matter ....Pages i-xiii
Preliminaries (Vladas Pipiras, Murad S. Taqqu)....Pages 1-9
Minimality, Rigidity, and Flows (Vladas Pipiras, Murad S. Taqqu)....Pages 11-48
Mixed Moving Averages and Self-Similarity (Vladas Pipiras, Murad S. Taqqu)....Pages 49-114
Back Matter ....Pages 115-135

✦ Subjects

Stochastic processes;MATHEMATICS / Applied;MATHEMATICS / Probability & Statistics / General;Mathematics;Probability Theory and Stochastic Processes;Dynamical Systems and Ergodic Theory