Modeling lifetime data with application to fatigue models
Modeling lifetime data with application to fatigue models
复制标题
对寿命数据进行建模并应用于疲劳模型
DOI：
10.1080/01621459.1995.10476606
复制
发表时间：
1995
影响因子：
3.7
通讯作者：
A. Hadi
中科院分区：
文献类型：
--
作者：
E. Castillo;A. Hadi
摘要基于物理和统计学的考虑，导出了一个新的模型，用于分析存在协变量的寿命数据。该模型依赖于五个具有明确物理解释的参数。给出了参数估计和分位数估计的两种方法：一种是基于阶统计量的方法，另一种是基于回归估计量的方法。分位数估计量以及五个参数中的四个参数的估计量以封闭形式给出。第五个参数可以用封闭形式或简单的数值算法独立于其他参数进行估计。仿真研究表明，回归估计量对参数的估计效果较好，而阶统计量估计量对低分位数的估计效果较好。该方法还通过一个实际数据实例加以说明。
Abstract A new model for the analysis of lifetime data in the presence of a covariate is derived based on physical and statistical considerations. The model depends on five parameters that have clear physical interpretations. Two methods for the estimation of the parameters and of the quantiles are presented: one based on the order statistics and the other a regression estimator. The quantile estimators as well as the estimators of four of the five parameters are given in closed form. The fifth parameter can be estimated independently of the other parameters using either a closed form or a numerically simple algorithm. A simulation study shows that the regression estimators are better for estimating the parameters but the order statistics estimators perform better for the estimation of low quantiles. The methodology is also illustrated by an example of a real life data.