Parameter Estimation for the Exponentiated Kumaraswamy-Power Function Distribution Based on Order Statistics with Application

Devendra Kumar (), Neetu Jain, Mazen Nassar and Osama Eraki Abo-Kasem
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Devendra Kumar: Central University of Haryana
Neetu Jain: University of Delhi
Mazen Nassar: King Abdulaziz University
Osama Eraki Abo-Kasem: Zagazig University

Annals of Data Science, 2021, vol. 8, issue 4, No 7, 785-811

Abstract: Abstract Exponentiated Kumaraswamy-power function (EKPF) distribution has been proposed recently by Bursa and Ozel (Hacet J Math Stat 46:277–292, 2017) as a quite flexible in terms of probability density and hazard rate functions than power function distribution. In this paper, we obtain the explicit expressions for the single, double (product), triple and quadruple moments and moment generating function for single, double, triple and quadruple of order statistics of the EKPF distribution. By using these relations, we have tabulated the means and variances of order statistics from samples of sizes up to 10 for various values of the parameters. We use five frequentist estimation methods to estimate the unknown parameters and a simulation study is used to compare the performance of the different estimators. Finally, we analyse a real data set for illustrative purpose.

Keywords: Exponentiated Kumaraswamy-power function; Order statistics; Moments and moment generating function; Estimations; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s40745-019-00233-4

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