Systems of components have a structure that plays an important role in determining how the reliability of the individual components relates to the reliability of the system. The system reliability can be computed from component reliabilities using results from basic probability theory in the simplest case with all of the components assumed to act independently of one another. However, in the case of dependence, such calculations can be much more involved. When reliability data have been independently collected on both the system and each component in the system, it can be difficult to model any possible dependence between components. Established methods use the known structure of a system, along with these data, to assess whether the reliability of the individual components are mutually independent. In this paper, we expand this methodology to include an assessment of the type of dependence that may exist between the components. This is based on finding the system structure that would most likely produce the observed reliability data, under independence. In the frequentist setting, the likelihood approach is used to find these structures and an observed confidence measure is used to assess the strength of the statistical evidence in favor of each possible structure. In the Bayesian setting, posterior probabilities along with Bayes factors are used. An example demonstrates how these methods can be used in an applied setting.

中文翻译：

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基于可靠性数据的操作系统结构评估

组件系统的结构在确定各个组件的可靠性与系统可靠性之间的关系方面起着重要作用。在最简单的情况下，可以使用基本概率理论的结果从组件可靠性中计算系统可靠性，假设所有组件相互独立。然而，在依赖的情况下，这种计算可能会涉及更多。当在系统和系统中的每个组件上独立收集可靠性数据时，就很难对组件之间的任何可能的依赖关系建模。已建立的方法使用系统的已知结构以及这些数据来评估各个组件的可靠性是否相互独立。在本文中，我们扩展了这种方法以包括对组件之间可能存在的依赖类型的评估。这是基于在独立的情况下找到最有可能产生观察到的可靠性数据的系统结构。在频率论设置中，似然方法用于查找这些结构，并使用观察到的置信度度量来评估支持每种可能结构的统计证据的强度。在贝叶斯设置中，使用后验概率和贝叶斯因子。一个示例演示了如何在应用设置中使用这些方法。似然方法用于找到这些结构，并使用观察到的置信度来评估支持每种可能结构的统计证据的强度。在贝叶斯设置中，使用后验概率和贝叶斯因子。一个示例演示了如何在应用设置中使用这些方法。似然方法用于找到这些结构，并使用观察到的置信度来评估支持每种可能结构的统计证据的强度。在贝叶斯设置中，使用后验概率和贝叶斯因子。一个示例演示了如何在应用设置中使用这些方法。