Data-driven semi-parametric detection of multiple changes in long-range dependent processes

Jean-Marc Bardet (1) , Abdellatif Guenaizi

1 SAMM - Statistique, Analyse et Modélisation Multidisciplinaire (SAmos-Marin Mersenne)

This paper is devoted to the offline multiple changes detection for long-range dependence processes. The observations are supposed to satisfy a semi-parametric long-range dependence assumption with distinct memory parameters on each stage. A penalized local Whittle contrast is considered for estimating all the parameters, notably the number of changes. The consistency as well as convergence rates are obtained. Monte-Carlo experiments exhibit the accuracy of the estimators. They also show that the estimation of the number of breaks is improved by using a data-driven slope heuristic procedure of choice of the penalization parameter.

Mots clés: 62M10; 62M15; 62F12

Domaines: Statistiques [math.ST]

Jean-Marc Bardet, Abdellatif Guenaizi. Data-driven semi-parametric detection of multiple changes in long-range dependent processes. Electronic Journal of Statistics , In press. ⟨hal-01676967v2⟩