Information Generating Function of Ranked Set Samples

被引：4
|
作者：
Kharazmi, Omid [1 ]
Tamandi, Mostafa [1 ]
Balakrishnan, Narayanaswamy [2 ]
机构：
[1] Vali E Asr Univ Rafsanjan, Fac Math Sci, Dept Stat, POB 518, Rafsanjan, Iran
[2] McMaster Univ, Dept Math & Stat, Hamilton, ON L8S 4L8, Canada
来源：
ENTROPY | 2021年 / 23卷 / 11期
关键词：
information generating function; relative information generating function; Kullback-Leibler divergence; ranked set sampling; simple random sampling; FISHER INFORMATION;
D O I：
10.3390/e23111381
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
In the present paper, we study the information generating (IG) function and relative information generating (RIG) function measures associated with maximum and minimum ranked set sampling (RSS) schemes with unequal sizes. We also examine the IG measures for simple random sampling (SRS) and provide some comparison results between SRS and RSS procedures in terms of dispersive stochastic ordering. Finally, we discuss the RIG divergence measure between SRS and RSS frameworks.
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页数：12
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