Density deconvolution from repeated measurements without symmetry assumption on the errors - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Journal of Multivariate Analysis Année : 2015

Density deconvolution from repeated measurements without symmetry assumption on the errors

Résumé

We consider deconvolution from repeated observations with unknown error distribution. So far, this model has mostly been studied under the additional assumption that the errors are symmetric. We construct an estimator for the non-symmetric error case and study its theoretical properties and practical performance. It is interesting to note that we can improve substantially upon the rates of convergence which have so far been presented in the literature and, at the same time, dispose of most of the extremely restrictive assumptions which have been imposed so far.
Fichier principal
Vignette du fichier
Deconvolution_repeated_measurements.pdf (261.98 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01010409 , version 1 (19-06-2014)

Licence

Copyright (Tous droits réservés)

Identifiants

Citer

Fabienne Comte, Johanna Kappus. Density deconvolution from repeated measurements without symmetry assumption on the errors. Journal of Multivariate Analysis, 2015, 140, pp.31-46. ⟨10.1016/j.jmva.2015.04.004⟩. ⟨hal-01010409⟩
340 Consultations
519 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More