For the first time and by using an entire sample, we discussed the estimation of the unknown parameters , and and the system of stress-strength reliability for exponentiated inverted Weibull (EIW) distributions with an equivalent scale parameter supported eight methods. We will use maximum likelihood method, maximum product of spacing estimation (MPSE), minimum spacing absolute-log distance estimation (MSALDE), least square estimation (LSE), weighted least square estimation (WLSE), method of Cramér-von Mises estimation (CME), and Anderson-Darling estimation (ADE) when X and Y are two independent a scaled exponentiated inverted Weibull (EIW) distribution. Percentile bootstrap and bias-corrected percentile bootstrap confidence intervals are introduced. To pick the better method of estimation, we used the Monte Carlo simulation study for comparing the efficiency of the various estimators suggested using mean square error and interval length criterion. From cases of samples, we discovered that the results of the maximum product of spacing method are more competitive than those of the other methods. A two real‐life data sets are represented demonstrating how the applicability of the methodologies proposed in real phenomena.

中文翻译：

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指数倒威布尔分布的应力-强度可靠性及其在黄麻纤维和碳纤维断裂中的应用

我们第一次通过使用整个样本，讨论了未知参数的估计 ,和应力强度可靠性系统对于具有等效尺度参数的指数倒威布尔 (EIW) 分布，支持八种方法。我们将使用最大似然法、最大间距估计（MPSE）、最小间距绝对对数距离估计（MSALDE）、最小二乘估计（LSE）、加权最小二乘估计（WLSE）、Cramér-von Mises估计方法（ CME) 和 Anderson-Darling 估计 (ADE) 当X和Y是两个独立的缩放指数倒威布尔 (EIW) 分布。引入了百分位引导程序和偏差校正的百分位引导程序置信区间。为了选择更好的估计方法，我们使用蒙特卡罗模拟研究来比较使用均方误差和区间长度标准建议的各种估计器的效率。从样本案例中，我们发现间距法的最大乘积的结果比其他方法的结果更具竞争力。代表了两个现实生活中的数据集，展示了所提出的方法在现实现象中的适用性。