Title : ( Nonparametric Estimation of the Residual Entropy Function with Length-Biased Data )
Authors: Farzaneh Oliazadeh , Anis Iranmanesh , Vahid Fakoor ,
Full TextAbstract
We propose a nonparametric estimator for the residual entropy function based on length-biased data. Some asymptotic results have been proved. The strong consistency and asymptotic normality of the proposed estimator are established under suitable regularity conditions. Monte Carlo simulation studies are carried out to eval- uate the performance of the estimator using the bias and mean-squared error. A real data set is considered, and we show that the data follow a length-biased distribution. Moreover, the proposed estimator yields a better value for the estimated residual en- tropy in comparison to the competitor estimator.
Keywords
, Asymptotic Normality, Length-Biased Data, Kernel Density Estimation, Residual Entropy, Strong Consistency.
@article{paperid:1096855,
author = {فرزانه اولیا زاده and انیس ایرانمنش and Fakoor, Vahid},
title = {Nonparametric Estimation of the Residual Entropy Function with Length-Biased Data},
journal = {Journal of the Iranian Statistical Society},
year = {2022},
volume = {21},
number = {1},
month = {June},
issn = {1726-4057},
pages = {1--18},
numpages = {17},
keywords = {Asymptotic Normality; Length-Biased Data; Kernel Density Estimation; Residual Entropy; Strong Consistency.},
}
%0 Journal Article
%T Nonparametric Estimation of the Residual Entropy Function with Length-Biased Data
%A فرزانه اولیا زاده
%A انیس ایرانمنش
%A Fakoor, Vahid
%J Journal of the Iranian Statistical Society
%@ 1726-4057
%D 2022
