New Parametric Estimation Methods based on Ranked Set Sampling

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Gazi University Journal of Science
Volume:32 Issue:4
New Parametric Estimation Methods based on Ranked Set Sampling

New Parametric Estimation Methods based on Ranked Set Sampling

Authors : Mohamed ABDALLAH, Samir ASHOUR

Pages : 1356-1368

Doi:10.35378/gujs.477631

View : 25 | Download : 11

Publication Date : 2019-12-01

Article Type : Research Paper

Abstract :The problem of parameters estimation plays a significant role in various areas of academic researches. In this article, we propose three different methods of estimation for the parameters of location-scale family under ranked set sampling in the view of missing data mechanism. Through a series of Monte Carlo simulations, it is well investigated that the proposed methods are relatively robust from violating the perfect ranking condition and provide better performance over their competitors using bias and MSE insert ignore into journalissuearticles values(mean square error); criteria. An empirical data set is also used for illustrative purposes.
Keywords : Cramér von Mises, EM algorithm, Estimation methods, Missing Data Approach, Ranked set sampling

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