Properties and Examples

  • Paul Doukhan

Part of the Lecture Notes in Statistics book series (LNS, volume 85)

Table of contents

  1. Front Matter
    Pages n1-xii
  2. General properties

    1. Front Matter
      Pages 1-1
    2. Paul Doukhan
      Pages 3-5
    3. Paul Doukhan
      Pages 7-13
    4. Paul Doukhan
      Pages 15-23
    5. Paul Doukhan
      Pages 25-44
    6. Paul Doukhan
      Pages 45-53
  3. Examples

    1. Front Matter
      Pages 55-55
    2. Paul Doukhan
      Pages 57-62
    3. Paul Doukhan
      Pages 63-73
    4. Paul Doukhan
      Pages 75-86
    5. Paul Doukhan
      Pages 87-109
    6. Paul Doukhan
      Pages 111-123
  4. Back Matter
    Pages 125-n2

About this book


Mixing is concerned with the analysis of dependence between sigma-fields defined on the same underlying probability space. It provides an important tool of analysis for random fields, Markov processes, central limit theorems as well as being a topic of current research interest in its own right. The aim of this monograph is to provide a study of applications of dependence in probability and statistics. It is divided in two parts, the first covering the definitions and probabilistic properties of mixing theory. The second part describes mixing properties of classical processes and random fields as well as providing a detailed study of linear and Gaussian fields. Consequently, this book will provide statisticians dealing with problems involving weak dependence properties with a powerful tool.


Maxima Probability space Variance proof theorem

Authors and affiliations

  • Paul Doukhan
    • 1
  1. 1.Department of EconomyUniversity of Cergy-PontoiseCergy-PontoiseFrance

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag New York 1994
  • Publisher Name Springer, New York, NY
  • eBook Packages Springer Book Archive
  • Print ISBN 978-0-387-94214-8
  • Online ISBN 978-1-4612-2642-0
  • Series Print ISSN 0930-0325
  • Buy this book on publisher's site