Article Dans Une Revue International Journal of Stochastic Analysis Année : 2020

Nonparametric Recursive Method for Kernel-Type Function Estimators for Censored Data

Résumé

In the present paper we propose recursive general kernel-type estimators for spatial data defined by the stochastic approximation algorithm. We obtain the central limit theorem and strong pointwise convergence rate for the nonparametric recursive general kernel-type estimators under some mild conditions. Finally, we investigate the MISE of the proposed estimators and provide the optimal bandwidth.

Dates et versions

hal-02926580 , version 1 (31-08-2020)

Identifiants

Citer

Salim Bouzebda, Yousri Slaoui. Nonparametric Recursive Method for Kernel-Type Function Estimators for Censored Data. International Journal of Stochastic Analysis, 2020, 139, pp.103-114. ⟨10.31390/josa.1.3.04⟩. ⟨hal-02926580⟩
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