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Lecture Notes in Statistics

Dependence in Probability and Statistics

Editors: Bertail, Patrice, Doukhan, Paul, Soulier, Philippe (Eds.)

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About this book

This book gives a detailed account of some recent developments in the field of probability and statistics for dependent data. The book covers a wide range of topics from Markov chain theory and weak dependence with an emphasis on some recent developments on dynamical systems, to strong dependence in times series and random fields. A special section is devoted to statistical estimation problems and specific applications. The book is written as a succession of papers by some specialists of the field, alternating general surveys, mostly at a level accessible to graduate students in probability and statistics, and more general research papers mainly suitable to researchers in the field.

The first part of the book considers some recent developments on weak dependent time series, including some new results for Markov chains as well as some developments on new notions of weak dependence. This part also intends to fill a gap between the probability and statistical literature and the dynamical system literature. The second part presents some new results on strong dependence with a special emphasis on non-linear processes and random fields currently encountered in applications. Finally, in the last part, some general estimation problems are investigated, ranging from rate of convergence of maximum likelihood estimators to efficient estimation in parametric or non-parametric time series models, with an emphasis on applications with non-stationary data.

Patrice Bertail is researcher in statistics at CREST-ENSAE, Malakoff and Professor of Statistics at the University-Paris X. Paul Doukhan is researcher in statistics at CREST-ENSAE, Malakoff and Professor of Statistics at the University of Cergy-Pontoise. Philippe Soulier is Professor of Statistics at the University-Paris X.

Table of contents (20 chapters)

Table of contents (20 chapters)
  • Regeneration-based statistics for Harris recurrent Markov chains

    Pages 3-54

    Bertail, Patrice (et al.)

  • Subgeometric ergodicity of Markov chains

    Pages 55-64

    Douc, Randal (et al.)

  • Limit Theorems for Dependent U-statistics

    Pages 65-86

    Dehling, Herold

  • Recent results on weak dependence for causal sequences. Statistical applications to dynamical systems.

    Pages 87-104

    Prieur, Clémentine

  • Parametrized Kantorovich-Rubinštein theorem and application to the coupling of random variables

    Pages 105-121

    Dedecker, Jérôme (et al.)

Buy this book

eBook 117,69 €
price for Spain (gross)
  • ISBN 978-0-387-36062-1
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 145,59 €
price for Spain (gross)
  • ISBN 978-0-387-31741-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Dependence in Probability and Statistics
Editors
  • Patrice Bertail
  • Paul Doukhan
  • Philippe Soulier
Series Title
Lecture Notes in Statistics
Series Volume
187
Copyright
2006
Publisher
Springer-Verlag New York
Copyright Holder
Springer-Verlag New York
eBook ISBN
978-0-387-36062-1
DOI
10.1007/0-387-36062-X
Softcover ISBN
978-0-387-31741-0
Series ISSN
0930-0325
Edition Number
1
Number of Pages
VIII, 490
Number of Illustrations
40 b/w illustrations
Topics