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在基于逐步第一个失败审查数据的逆帕雷托分布的P (Y < X) 估计上

Randa Alharbi¹, Renu Garg², Indrajeet Kumar³

¹Department of Statistics, Faculty of Science, University of Tabuk, Tabuk, Saudia Arabia.

|November 30, 2023

概括

本研究估计了使用逆帕雷托分布 (IPD) 数据在渐进式第一次故障审查 (PFFC) 下的系统的应力强度可靠性 (SSR). 它比较了经典和贝叶斯方法,包括最大概率和马尔科夫链蒙特卡洛,以准确评估系统可靠性.

科学领域:

可靠性工程可靠性工程
统计建模统计建模
质量控制质量控制质量控制

背景情况:

应力强度可靠性 (SSR) 模型,量化P(Y < X),对于评估工程,医学和质量控制的系统完整性至关重要.
在可靠性研究中,逐渐第一次故障审查 (PFFC) 数据是常见的,需要强大的估计方法.
逆帕雷托分布 (IPD) 为可靠性分析中的应力和强度变量提供了一个灵活的模型.

研究的目的:

用古典和贝叶斯方法估计应力强度可靠性 (SSR).
在逐渐第一次故障审查 (PFFC) 逆帕雷托分布 (IPD) 数据下调查不同估计技术的性能.
通过模拟研究和现实世界数据应用提供实际见解.

主要方法:

使用最大概率 (ML) 和最大产品间距 (MPS) 方法进行SSR的估计.
根据ML估计,推导SSR的间隔估计.
贝叶斯对SSR的估计使用马尔科夫链蒙特卡洛 (MCMC) 近似与二次误差损失函数和马先验.
使用来自独立逆帕雷托分布 (IPD) 的逐渐第一次故障审查 (PFFC) 数据来计算应力 (X) 和强度 (Y).

主要成果:

对SSR的经典 (ML,MPS) 和贝叶斯式 (MCMC) 估计器的准确性和效率进行比较.
评估不同审查方案对可靠性估计的影响.
使用模拟和真实数据集,展示开发方法的实际适用性.

结论:

经典和贝叶斯方法都在PFFC IPD数据下为SSR提供了有价值的估计.
估计方法和审查方案的选择可以显著影响可靠性评估.
该研究为SSR估计提供了全面的框架,增强了各个领域的系统可靠性分析.

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