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Selecting a Component with Longer Mean Life Time in Bivariate Pareto Models

机译:在双变量Pareto模型中选择平均寿命更长的组件

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In any parallel system, selecting a component with longer mean lifetime is of interest to the researchers. Hanagal (1997) [1] discussed selection procedures for a two-component system with bivariate exponential (BVE) models. In this paper, the problem of selecting a better component with reference to its mean life time under bivariate Pareto (BVP) models is considered. Three selection procedures based on sample proportions, sample means and maximum likelihood estimators (MLE) are proposed. The probability of correct selection for the proposed procedures is evaluated through Monte Carlo simulation using normal approximation. The asymptotic relative efficiency (ARE) of the proposed procedures is presented to facilitate the evaluation of the performance of procedures.
机译:在任何并行系统中,选择具有更长平均寿命的组件都是研究人员感兴趣的。 Hanagal(1997)[1]讨论了具有双变量指数(BVE)模型的两组件系统的选择程序。在本文中,考虑了在双变量Pareto(BVP)模型下参照其平均寿命选择更好的组件的问题。提出了基于样本比例,样本均值和最大似然估计(MLE)的三种选择程序。通过使用正态近似的蒙特卡罗模拟评估为所建议的程序选择正确的可能性。提出了拟议程序的渐近相对效率(ARE),以促进对程序性能的评估。

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