Kernel Estimation of Entropy Function for Length-Biased Censored Data

被引：1
|
作者：
Rajesh, G. [1 ]
Rajesh, Richu [1 ]
Sunoj, S. M. [1 ]
机构：
[1] Cochin Univ Sci & Technol, Dept Stat, Cochin 682022, Kerala, India
来源：
JOURNAL OF THE INDIAN SOCIETY FOR PROBABILITY AND STATISTICS | 2021年 / 22卷 / 02期
关键词：
Shannon entropy; Length-biased sampling; Censored data; Kernel density estimation; Mean squared error; NONPARAMETRIC-ESTIMATION; RESIDUAL ENTROPY; DURATION;
D O I：
10.1007/s41096-021-00103-4
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In this article, we propose nonparametric kernel type estimators for the Shannon differential entropy for length-biased censored data. The asymptotic properties of the estimators are established under specific regularity conditions. The performance of the estimators is examined through simulated observations and is compared using mean squared errors for various sample sizes. The applicability of the estimators is demonstrated using real data.
引用
收藏
页码：251 / 263
页数：13
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