A note on the strong consistency of nonparametric estimation of Shannon entropy in length-biased sampling

被引：2
|
作者：
Oliazadeh, Farzaneh [1 ]
Iranmanesh, Anis [1 ]
Fakoor, Vahid [2 ]
机构：
[1] Islamic Azad Univ, Dept Math & Stat, Mashhad Branch, Mashhad, Razavi Khorasan, Iran
[2] Ferdowsi Univ Mashhad, Fac Math Sci, Dept Stat, Mashahd, Iran
来源：
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2021年 / 50卷 / 24期
关键词：
Length-biased data; Kernel density estimation; Shannon entropy; strong consistency; KERNEL DENSITY-ESTIMATION; BANDWIDTH CONSISTENCY; UNIFORM;
D O I：
10.1080/03610926.2020.1737123
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 an estimator of Shannon entropy based on kernel estimators of density function in length-biased setting. The strong consistency of the proposed estimators is established. In addition, some simulations are conducted to evaluate the performance of the proposed estimator.
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页码：5779 / 5791
页数：13
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