In:
Statistics, Optimization & Information Computing, International Academic Press, Vol. 11, No. 2 ( 2023-02-17), p. 196-215
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
2310-5070
,
2311-004X
DOI:
10.19139/soic-2310-5070-1678
Language:
Unknown
Publisher:
International Academic Press
Publication Date:
2023
detail.hit.zdb_id:
2832885-1
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