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Parameter Estimation of the Exponentiated Pareto Distribution Using Ranked Set Sampling and Simple Random Sampling
Department of Statistics, Faculty of Mathematics-Statistics and Computer Science, University of Tabriz, Iran.ORCID iD: 0000-0003-0902-0967
Faculty of Business Management, Vilnius Gediminas Technical University, Vilnius, Lithuania.ORCID iD: 0000-0003-0435-7632
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. Division of Industrial Engineering and Management, Department of Civil and Industrial Engineering, Uppsala University, Sweden. (Produktion och automatiseringsteknik (PAT), Production and Automation Engineering)ORCID iD: 0000-0001-5530-3517
Institute of Business and Economics, Faculty of Public Governance and Business, Mykolas Romeris University, Vilnius, Lithuania.ORCID iD: 0000-0002-0079-9508
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2022 (English)In: Axioms, E-ISSN 2075-1680, Vol. 11, no 6, p. 1-9, article id 293Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
MDPI, 2022. Vol. 11, no 6, p. 1-9, article id 293
Keywords [en]
efficiency, exponentiated Pareto distribution, maximum likelihood estimator, order statistics, ranked set sampling, simple random sampling
National Category
Mathematics
Research subject
Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-21269DOI: 10.3390/axioms11060293ISI: 000816488100001Scopus ID: 2-s2.0-85132774324OAI: oai:DiVA.org:his-21269DiVA, id: diva2:1671836
Note

CC BY 4.0

Correspondence: ieva.meidute-kavaliauskiene@vilniustech.lt

Funding: This research received no external funding

Available from: 2022-06-17 Created: 2022-06-17 Last updated: 2022-08-31Bibliographically approved

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Fathi, Masood

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Khamnei, Hossein JabbariMeidute-Kavaliauskiene, IevaFathi, MasoodValackienė, AstaGhorbani, Shahryar
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