Improved Estimation of the Inverted Kumaraswamy Distribution Parameters Based on Ranked Set Sampling with an Application to Real Data

Heba F. Nagy (), Amer Ibrahim Al-Omari (), Amal S. Hassan and Ghadah A. Alomani
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Heba F. Nagy: Faculty of Graduate Studies for Statistical Research, Cairo University, Giza 12613, Egypt
Amer Ibrahim Al-Omari: Department of Mathematics, Faculty of Science, Al Al-Bayt University, Mafraq 25113, Jordan
Amal S. Hassan: Faculty of Graduate Studies for Statistical Research, Cairo University, Giza 12613, Egypt
Ghadah A. Alomani: Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia

Mathematics, 2022, vol. 10, issue 21, 1-19

Abstract: The ranked set sampling (RSS) methodology is an effective technique of acquiring data when measuring the units in a population is costly, while ranking them is easy according to the variable of interest. In this article, we deal with an RSS-based estimation of the inverted Kumaraswamy distribution parameters, which is extensively applied in life testing and reliability studies. Some estimation techniques are regarded, including the maximum likelihood, the maximum product of spacing’s, ordinary least squares, weighted least squares, Cramer–von Mises, and Anderson–Darling. We demonstrate a simulation investigation to assess the performance of the suggested RSS-based estimators via accuracy measures relative to simple random sampling. On the basis of actual data regarding the waiting times between 65 consecutive eruptions of Kiama Blowhole, additional conclusions have been drawn. The outcomes of simulation and real data application demonstrated that RSS-based estimators outperformed their simple random sampling counterparts significantly based on the same number of measured units.

Keywords: ranked set sampling; inverted Kumaraswamy distribution; maximum product spacing; maximum likelihood; Cramer–von Mises (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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