Dependence in probability and statistics

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...

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Detalles Bibliográficos
Autor Principal: Bertail, Patrice, 1964-
Outros autores: Doukhan, Paul, 1955- (Directeur de la publication), Soulier, Philippe, 19..-...., statisticien (Directeur de la publication)
Formato: Livre numérique
Idioma:Anglais
Publicado: New York, NY : Springer New York [20..].
Cham : Springer Nature
Edición:1st ed. 2006.
Series:Lecture Notes in Statistics 187
Sujets:
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Nota: Description d'après consultation du 17 mars 2011
Archives Springer e-books (Licence nationale)
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Edition sous un autre format:• Dependence in probability and statistics, Patrice Bertail, Paul Doukhan, Philippe Soulier (editors), 2006, New York (N.Y.), Springer, 1 vol. (VIII-492 p.), Lecture notes in statistics, 0-387-31741-4
• Dependence in Probability and Statistics, Texte imprimé, 9780387511948
• Dependence in probability and statistics, Patrice Bertail, Paul Doukhan, Philippe Soulier (editors), 2006, New York (N.Y.), Springer, 1 vol. (VIII-492 p.), Lecture notes in statistics, 0-387-31741-4
Descripción
Résumé: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
descrición da copia:Description d'après consultation du 17 mars 2011
Archives Springer e-books (Licence nationale)
Archives Springer e-books (Licence nationale)
Bibliografía:Notes bibliogr. en fin de chapitres
ISBN:9780387360621 (PDF)
ISSN:2197-7186
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