Novel entropy estimators of a continuous random variable

被引：9

作者：

Al-Omari, Amer Ibrahim ^{[1
]}

Haq, Abdul ^{[2
]}

机构：

[1] Al Al Bayt Univ, Fac Sci, Dept Math, Mafraq 25113, Jordan

[2] Quaid I Azam Univ, Dept Stat, Islamabad 45320, Pakistan

来源：

INTERNATIONAL JOURNAL OF MODELING SIMULATION AND SCIENTIFIC COMPUTING | 2019年 / 10卷 / 02期

关键词：

Entropy; bias; root mean-squared error; double ranked set sampling; ranked set sampling; simple random sampling; GENERALIZED MAXIMUM-ENTROPY; INFORMATION; TESTS; FIT;

D O I：

10.1142/S1793962319500041

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This paper presents some novel entropy estimators of a continuous random variable using simple random sampling (SRS), ranked set sampling (RSS), and double RSS (DRSS) schemes. The theoretical results of the proposed entropy estimators are derived. The proposed entropy estimators are compared in terms of the bias and the root mean squared errors, theoretically and numerically, with the Vasicek O. [A test for normality based on sample entropy, J. R. Stat. Soc. B 38: 54-59, 1976.] entropy estimators using SRS, RSS, and DRSS schemes. It turns out that the new novel entropy estimators are substantially better than the existing Vasicek's entropy estimators.

引用

页数：19

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