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Article Dans Une Revue Statistics, Optimization and Information Computing Année : 2023

Nonparametric Recursive Kernel Type Eestimators for the Moment Generating Function Under Censored Data

Résumé

We are mainly concerned with kernel-type estimators for the moment-generating function in the present paper. More precisely, we establish the central limit theorem with the characterization of the bias and the variance for the nonparametric recursive kernel-type estimators for the moment-generating function under some mild conditions in the censored data setting. Finally, we investigate the methodology's performance for small samples through a short simulation study.
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Dates et versions

hal-04389539 , version 1 (18-01-2024)

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Salim Bouzebda, Issam Elhattab, Yousri Slaoui Slaoui, Nourelhouda Taachouche. Nonparametric Recursive Kernel Type Eestimators for the Moment Generating Function Under Censored Data. Statistics, Optimization and Information Computing, 2023, 11 (2), pp.196 - 215. ⟨10.19139/soic-2310-5070-1678⟩. ⟨hal-04389539⟩
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