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Nonparametric estimation of marginal failure distributions from dually censored automotive data

机译:来自双义汽车数据的边缘故障分布的非参数估计

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摘要

It is not uncommon that a component's reliability characteristics depend on two usage variables. As an example, for automotive components such variables are time in service and accumulated mileage. For certain airplane chassis components, these variables are accumulated flight hours and the number of landings. The problem of failure time distribution estimation from dually censored (at warranty limits) automotive data has been addressed by many authors. However, most of published work is focused on estimating marginal in time failure distributions or (less frequently) joint failure distributions. This paper focuses on nonparametric estimation of the marginal in mileage failure distributions, since for the majority of the automotive components mileage is considered a more relevant survival variable than time in service.
机译:组件的可靠性特性取决于两个使用变量并不罕见。例如,对于汽车组件,这种变量是服务中的时间和累积的里程。对于某些飞机底盘组件,这些变量是累积的飞行时间和着陆的数量。许多作者都有许多作者解决了双重被审查(在保修范围)汽车数据的故障时间分布估计问题。但是,大多数已发表的工作都集中在时间故障分布或(较不频繁地)联合失败分布的边际。本文重点介绍了在线故障分布的边际的非参数估计,因为对于大多数汽车组件的里程被认为是比服务中的时间更相关的生存变量。

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