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Metrika 69, 2-3 (2009) 199-225
Weak dependence, models and some applications
Paul Doukhan 1, 2, Nathanaël Mayo 2, Lionel Truquet 1, 2, 3, 4
(2009-03)

The paper is devoted to recall weak dependence conditions from Dedecker et al. (Weak dependence, examples and applications. Lecture Notes in Statistics, vol 190, 2007)'s monograph; the main basic results are recalled here and we go further in some new applications. We develop here several models of weakly dependent processes and random fields. Among them an ARCH(∞) model is considered with statistical applications to ordinary least squares. A last part aims at proving new asymptotic results for weakly dependent random fields. Such applications are indeed the main proof of the interest of this theoretical notion which measures the asymptotic decorrelation of a process.
1:  Centre d'économie de la Sorbonne (CES)
CNRS : UMR8174 – Université Paris I - Panthéon-Sorbonne
2:  Statistique Appliquée et MOdélisation Stochastique (SAMOS)
Université Paris I - Panthéon-Sorbonne
3:  Centre de Recherche en Économie et Statistique (CREST)
INSEE – École Nationale de la Statistique et de l'Administration Économique
4:  Institut de Recherche Mathématique de Rennes (IRMAR)
CNRS : UMR6625 – Université de Rennes 1 – École normale supérieure de Cachan - ENS Cachan – Institut National des Sciences Appliquées (INSA) : - RENNES – Université de Rennes II - Haute Bretagne
Mathematics/Statistics

Statistics/Statistics Theory
Weak dependence - Asymptotic properties of estimators - Random fields - Functional limit theorems - Invariance principles