Parameter Estimation of the Exponentiated Pareto Distribution Using Ranked Set Sampling and Simple Random Sampling

被引：3

作者：

Khamnei, Hossein Jabbari ^{[1
]}

Meidute-Kavaliauskiene, Ieva ^{[2
]}

Fathi, Masood ^{[3
,4
]}

Valackiene, Asta ^{[5
]}

Ghorbani, Shahryar ^{[6
]}

机构：

[1] Univ Tabriz, Fac Math Stat & Comp Sci, Dept Stat, Tabriz 5166616471, Iran

[2] Vilnius Gediminas Tech Univ, Fac Business Management, Sauletekio Al 11, LT-10223 Vilnius, Lithuania

[3] Univ Skovde, Sch Engn Sci, Div Intelligent Prod Syst, S-54128 Skovde, Sweden

[4] Uppsala Univ, Dept Civil & Ind Engn, Div Ind Engn & Management, S-75121 Uppsala, Sweden

[5] Mykolas Romeris Univ, Inst Business & Econ, Fac Publ Governance & Business, Ateities St 20,Room C 5-509, LT-08303 Vilnius, Lithuania

[6] Univ Sakarya, Prod Management Dept, TR-54050 Sakarya, Turkey

来源：

AXIOMS | 2022年 / 11卷 / 06期

关键词：

efficiency; exponentiated Pareto distribution; maximum likelihood estimator; order statistics; ranked set sampling; simple random sampling; ORDER-STATISTICS;

D O I：

10.3390/axioms11060293

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper, we have considered that ranked set sampling is able to estimate the parameters of exponentiated Pareto distribution. The method with which the maximum likelihood estimators for the parameters of exponentiated Pareto distribution is studied is numerical since there is no presence or possibility of a closed-form at the hands of estimators or any other intellectual. The numerical approach is a well-suited one for this study as there has been struggles in achieving it with any other technique. In order to compare the different sampling methods, simulation studies are performed as the main technique. As for the illustrative purposes, analysis of a simulated dataset is desired for the objective of the presentation. The conclusion that we can reach based on these is that the estimators based on the ranked set sample have far better efficiency than the simple random sample at the same sample size.

引用

页数：9

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