Long-Range Dependence and Self-Similarity
eBook - PDF

Long-Range Dependence and Self-Similarity

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Long-Range Dependence and Self-Similarity

Book details
Table of contents
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About This Book

This modern and comprehensive guide to long-range dependence and self-similarity starts with rigorous coverage of the basics, then moves on to cover more specialized, up-to-date topics central to current research. These topics concern, but are not limited to, physical models that give rise to long-range dependence and self-similarity; central and non-central limit theorems for long-range dependent series, and the limiting Hermite processes; fractional Brownian motion and its stochastic calculus; several celebrated decompositions of fractional Brownian motion; multidimensional models for long-range dependence and self-similarity; and maximum likelihood estimation methods for long-range dependent time series. Designed for graduate students and researchers, each chapter of the book is supplemented by numerous exercises, some designed to test the reader's understanding, while others invite the reader to consider some of the open research problems in the field today.

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Yes, you can access Long-Range Dependence and Self-Similarity by Vladas Pipiras,Murad S. Taqqu in PDF and/or ePUB format, as well as other popular books in Matemáticas & Probabilidad y estadística. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Cambridge University Press
Year
2017
ISBN
9781108215596
Topic
Matemáticas
Subtopic
Probabilidad y estadística

Table of contents

  1. Cover
  2. Half-title page
  3. Series page
  4. Title page
  5. Copyright page
  6. Dedication
  7. Contents
  8. Expanded Contents
  9. List of Abbreviations
  10. Notation
  11. Preface
  12. 1 A Brief Overview of Time Series and Stochastic Processes
  13. 2 Basics of Long-Range Dependence and Self-Similarity
  14. 3 Physical Models for Long-Range Dependence and Self-Similarity
  15. 4 Hermite Processes
  16. 5 Non-Central and Central Limit Theorems
  17. 6 Fractional Calculus and Integration of Deterministic Functions with Respect to FBM
  18. 7 Stochastic Integration with Respect to Fractional BrownianMotion
  19. 8 Series Representations of Fractional Brownian Motion
  20. 9 Multidimensional Models
  21. 10 Maximum Likelihood Estimation Methods
  22. A Auxiliary Notions and Results
  23. B Integrals with Respect to Random Measures
  24. C Basics of Malliavin Calculus
  25. D Other Notes and Topics
  26. Bibliography
  27. Index