Nonparametric -Divergence Estimation and Test for Model Selection

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AuteurDJIBRIL MOUSSA, FREEDATH LAYE ERI YOMI
AuteurNKURUNZIZA, JEAN DE DIEU
AuteurNGOM, PAPA
Date d'ajout2026-06-02T16:06:57Z
Date de disponibilite2026-06-02T16:06:57Z
Date de publication2020
ResumeIn this paper, we study a bias reduced kernel density estimator and derive a nonparametric -divergence estimator based on this density estimator. We investigate the asymptotic properties of these two estimators and we formulate an asymptotically standard normal test for model selection.
Autre identifiantBECDB-14923
URIhttps://dspace.uac.bj/handle/123456789/12690
Languefr
Fait partie deAfrika Statistika
Sujetnonparametric estimation
Sujetdivergence
Sujetstrong consistency
Sujetasymptotic
Sujetnormality
Sujethypothesis testing
Sujetmodel Selection
TitreNonparametric -Divergence Estimation and Test for Model Selection
TypeArticle

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