Polygonal smoothing of the empirical distribution function - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Statistical Inference for Stochastic Processes Année : 2018

Polygonal smoothing of the empirical distribution function

Résumé

We present two families of polygonal estimators of the distribution function: the first family is based on the knowledge of the support while the second addresses the case of an unknown support. Polygonal smoothing is a simple and natural method for regularizing the empirical distribution function Fn but its properties have not been studied deeply. First, consistency and exponential type inequalities are derived from well-known convergence properties of Fn. Then, we study their mean integrated squared error (MISE) and we establish that polygonal estimators may improve the MISE of Fn. We conclude by some numerical results to compare these estimators globally, and also together with the integrated kernel distribution estimator.
Fichier principal
Vignette du fichier
polygonal_cdf_preprint.pdf (1.04 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02062903 , version 1 (10-03-2019)

Identifiants

Citer

Delphine Blanke, Denis Bosq. Polygonal smoothing of the empirical distribution function. Statistical Inference for Stochastic Processes, 2018, 21 (2), pp.263-287. ⟨10.1007/s11203-018-9183-y⟩. ⟨hal-02062903⟩
100 Consultations
294 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More