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Volume 11
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Article

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

by
Hossein Jabbari Khamnei
1,
Ieva Meidute-Kavaliauskiene
2,*,
Masood Fathi
3,4,
Asta Valackienė
5 and
Shahryar Ghorbani
6
1
Department of Statistics, Faculty of Mathematics-Statistics and Computer Science, University of Tabriz, Tabriz 5166616471, Iran
2
Faculty of Business Management, Vilnius Gediminas Technical University, Sauletekio al. 11, 10223 Vilnius, Lithuania
3
Division of Intelligent Production Systems, School of Engineering Science, University of Skövde, 54128 Skövde, Sweden
4
Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, 75121 Uppsala, Sweden
5
Institute of Business and Economics, Faculty of Public Governance and Business, Mykolas Romeris University, Ateities Street 20, Room C-V-509, 08303 Vilnius, Lithuania
6
Production Management Department, University of Sakarya, Sakarya 54050, Turkey
*
Author to whom correspondence should be addressed.
Axioms 2022, 11(6), 293; https://doi.org/10.3390/axioms11060293
Submission received: 24 May 2022 / Revised: 9 June 2022 / Accepted: 11 June 2022 / Published: 15 June 2022
(This article belongs to the Special Issue Multiple-Criteria Decision-Making and Computational Intelligence: Recent Applications)
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Abstract

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.
Keywords: efficiency; exponentiated Pareto distribution; maximum likelihood estimator; order statistics; ranked set sampling; simple random sampling efficiency; exponentiated Pareto distribution; maximum likelihood estimator; order statistics; ranked set sampling; simple random sampling

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MDPI and ACS Style

Khamnei, H.J.; Meidute-Kavaliauskiene, I.; Fathi, M.; Valackienė, A.; Ghorbani, S. Parameter Estimation of the Exponentiated Pareto Distribution Using Ranked Set Sampling and Simple Random Sampling. Axioms 2022, 11, 293. https://doi.org/10.3390/axioms11060293

AMA Style

Khamnei HJ, Meidute-Kavaliauskiene I, Fathi M, Valackienė A, Ghorbani S. Parameter Estimation of the Exponentiated Pareto Distribution Using Ranked Set Sampling and Simple Random Sampling. Axioms. 2022; 11(6):293. https://doi.org/10.3390/axioms11060293

Chicago/Turabian Style

Khamnei, Hossein Jabbari, Ieva Meidute-Kavaliauskiene, Masood Fathi, Asta Valackienė, and Shahryar Ghorbani. 2022. "Parameter Estimation of the Exponentiated Pareto Distribution Using Ranked Set Sampling and Simple Random Sampling" Axioms 11, no. 6: 293. https://doi.org/10.3390/axioms11060293

APA Style

Khamnei, H. J., Meidute-Kavaliauskiene, I., Fathi, M., Valackienė, A., & Ghorbani, S. (2022). Parameter Estimation of the Exponentiated Pareto Distribution Using Ranked Set Sampling and Simple Random Sampling. Axioms, 11(6), 293. https://doi.org/10.3390/axioms11060293

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