Estimation of a Parallel Stress-strength Model Based on the Inverse Kumaraswamy Distribution

Authors

Bayda A. Kalaf Department of Mathematics, College of Education for Pure Sciences, Ibn Al – Haitham, University of Baghdad
Bsma Abdul Hameed Ministry of Education, Directorate of Education, Rusafa second, Baghdad, Iraq
Abbas N. Salman Department of Mathematics, College of Education for Pure Sciences, Ibn Al – Haitham, University of Baghdad Iraq
Erum Rehman GEEDS-Group of energy, economy and system dynamics. University of Valladolid, Spain

DOI:

https://doi.org/10.30526/36.1.2972

Keywords:

Invers Kumaraswamy distribution, Stress ـ Strength reliability, Shrinkage estimator, Mean Squared Error

Abstract

The reliability of the stress-strength model attracted many statisticians for several years owing to its applicability in different and diverse parts such as engineering, quality control, and economics. In this paper, the system reliability estimation in the stress-strength model containing Kth parallel components will be offered by four types of shrinkage methods: constant Shrinkage Estimation Method, Shrinkage Function Estimator, Modified Thompson Type Shrinkage Estimator, Squared Shrinkage Estimator. The Monte Carlo simulation study is compared among proposed estimators using the mean squared error. The result analyses of the shrinkage estimation methods showed that the shrinkage functions estimator was the best since it has a minor mean squared error than the other methods followed by the additional shrinkage estimator. The stress and strength belong to the In

verse Kumaraswamy distribution

Author Biographies

Bayda A. Kalaf, Department of Mathematics, College of Education for Pure Sciences, Ibn Al – Haitham, University of Baghdad
Bsma Abdul Hameed, Ministry of Education, Directorate of Education, Rusafa second, Baghdad, Iraq
Abbas N. Salman, Department of Mathematics, College of Education for Pure Sciences, Ibn Al – Haitham, University of Baghdad Iraq
Erum Rehman , GEEDS-Group of energy, economy and system dynamics. University of Valladolid, Spain

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