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

B. A. Kalaf, Bsma Abdul Hameed, Abbas N. Salman, Erum Rehman
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引用次数: 0

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
基于逆Kumaraswamy分布的平行应力-强度模型估计
近年来,由于应力强度模型在工程、质量控制和经济等不同领域的适用性,其可靠性问题引起了众多统计学家的关注。本文将采用恒收缩估计法、收缩函数估计法、修正汤普森型收缩估计法、平方收缩估计法四种收缩方法对含有k个平行分量的应力-强度模型进行系统可靠性估计。利用均方误差对所提出的估计量进行了蒙特卡罗模拟研究。对收缩估计方法的结果分析表明,收缩函数估计方法的均方误差较小,优于其他方法,其次是附加收缩估计方法。应力和强度属于逆库马拉斯瓦米分布
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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67
审稿时长
18 weeks
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