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Stable Non-Gaussian Self-Similar Processes with Stationary Increments

  • Vladas Pipiras
  • Murad S. Taqqu

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Vladas Pipiras, Murad S. Taqqu
    Pages 1-9
  3. Vladas Pipiras, Murad S. Taqqu
    Pages 11-48
  4. Vladas Pipiras, Murad S. Taqqu
    Pages 49-114
  5. Back Matter
    Pages 115-135

About this book

Introduction

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.

Keywords

Symmetric Stable Processes Self-Similarity Stationarity of Increments Mixed Moving Averages Minimality Rigidity Isometries Non-singular Flows and their Functionals

Authors and affiliations

  • Vladas Pipiras
    • 1
  • Murad S. Taqqu
    • 2
  1. 1.Statistics and Operations ResearchUniversity of North Carolina at Chapel HillChapel HillUSA
  2. 2.Department of Mathematics and StatisticsBoston UniversityBostonUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-62331-3
  • Copyright Information The Author(s) 2017
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-62330-6
  • Online ISBN 978-3-319-62331-3
  • Series Print ISSN 2365-4333
  • Series Online ISSN 2365-4341
  • Buy this book on publisher's site