Dependence in Probability and Statistics
Language: English
Published by Springer, Springer Mai 2006, 2006
- Softcover
- New
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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This item is printed on demand - Print on Demand Titel. Neuware -This book gives a detailed account of recent developments in the field of probability and statistics for dependent data. It 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 section is devoted to statistical estimation problems and specific applications. The book is written as a succession of papers by field specialists, 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 book considers recent developments on weak dependent time series, including some new results for Markov chains, and fills a gap between the probability and statistical literature and the dynamical system literature. The book also presents new results on strong dependence with an emphasis on non-linear processes and random fields.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 504 pp. Englisch.…
Seller Inventory # 9780387317410
- Title
- Dependence in Probability and Statistics
- Author
- Patrice Bertail
- Publisher
- Springer, Springer Mai 2006
- Publication year
- 2006
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0387317414
- ISBN 13
- 9780387317410
- Item weight
- 756 grams
- Dimensions
- 235x155x28 mm
- Series
- Book 33 of 72: Lecture Notes in Statistics
"Synopsis" may belong to another edition of this title.
From the Back Cover
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.
"About the title" may belong to another edition of this title.
buchversandmimpf2000
Emtmannsberg, BAYE, Germany
AbeBooks seller since January 23, 2017
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