Smoothed kernel estimation of bivariate residual entropy function

被引：2

作者：

Rajesh, G. ^{[1
]}

Joseph, Linto ^{[1
]}

Jacob, T. M. ^{[2
]}

机构：

[1] Cochin Univ Sci & Technol, Dept Stat, Cochin 682022, Kerala, India

[2] Nirmala Coll, Dept Stat, Muvattupuzha, India

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2023年 / 52卷 / 09期

关键词：

Bivariate residual entropy; Real data; Shannon entropy; Smoothed estimation; NONPARAMETRIC-ESTIMATION; EXPRESSIONS;

D O I：

10.1080/03610918.2021.1951764

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 for a bivariate residual entropy function based on smoothed kernel procedure. Asymptotic properties of the proposed estimator are established under some regularity conditions. Simulation studies demonstrate that the estimator performs well even for increased sample sizes and different combinations of lifetimes. The performances of the proposed estimator are tabulated and illustrated through a data on recurrence of cancer.

引用

页码：4065 / 4074

页数：10

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