Estimation of the lifetime distribution of mechatronic systems in the presence of a covariate: A comparison among parametric, semiparametric and nonparametric models
Estimation of the lifetime distribution of mechatronic systems in the presence of a covariate: A comparison among parametric, semiparametric and nonparametric models
复制标题
存在协变量时机电系统寿命分布的估计：参数、半参数和非参数模型之间的比较
DOI：
10.1016/j.ress.2015.02.012
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Schinköthe
中科院分区：
文献类型：
--
作者：
Bobrowski;Döring;Jensen;Schinköthe
在实际生产中，生产厂家可能会有大量使用相同技术基础的同类产品在不同工况下的故障数据。因此，可以尝试通过使用基于协变量的回归模型的现有数据，推导出对新开发组件或新应用程序环境的生命周期分布的预测。考虑了三种回归模型：参数、半参数和非参数方法。首先，我们假设寿命是威布尔分布的，其中其参数被建模为协变量的线性函数。其次，应用生存分析中著名的Cox比例风险模型。最后，利用核估计器在经验分布函数之间进行插值。特别是最后一种情况，在可靠性分析的背景下是新的。我们提出了一个拟合优度度量（GoF），它可以应用于所有三种类型的回归模型。利用这种GoF度量，我们讨论了一种新的模型选择过程。为了说明这种可靠性预测方法，将这三类回归模型应用于电机实验的实际测试数据。通过蒙特卡罗仿真进一步研究了方法的性能。
In practice manufacturers may have lots of failure data of similar products using the same technology basis under different operating conditions. Thus, one can try to derive predictions for the distribution of the lifetime of newly developed components or new application environments through the existing data using regression models based on covariates.Three categories of such regression models are considered: a parametric, a semiparametric and a nonparametric approach. First, we assume that the lifetime is Weibull distributed, where its parameters are modelled as linear functions of the covariate. Second, the Cox proportional hazards model, well-known in Survival Analysis, is applied. Finally, a kernel estimator is used to interpolate between empirical distribution functions. In particular the last case is new in the context of reliability analysis.We propose a goodness of fit measure (GoF), which can be applied to all three types of regression models. Using this GoF measure we discuss a new model selection procedure.To illustrate this method of reliability prediction, the three classes of regression models are applied to real test data of motor experiments. Further the performance of the approaches is investigated by Monte Carlo simulations.
带有删失协变量的非参数回归
影响因子：
1.6
作者：
D. Dabrowska
通讯作者：
D. Dabrowska
影响因子：
2.3
作者：
GLASER, RE
通讯作者：
GLASER, RE