论文标题
在间隔监视下对依赖竞争风险模型的强大估计并确定最佳检查间隔
Robust estimation of dependent competing risk model under interval monitoring and determining optimal inspection intervals
论文作者
论文摘要
最近，越来越多的兴趣在建模依赖竞争风险的风险中很明显。在这项工作中，我们建议通过元帅 - olkin双变量指数分布对依赖竞争风险进行建模。可观察到的数据包括由于不同时间间隔的不同原因而导致的故障数量。故障数数据在一个实例中很常见，例如在不同的检查时间检查受试者的状态而不是确切的故障时间。通过基于差异的稳健估计方法，研究了存在竞争风险的生命时间分布的点估计，称为最小密度功率差异估计（MDPDE）。假设的检验是根据WALD型测试统计量进行的。对点估计量和测试统计量既得出了影响函数，又反映了稳健性的程度。这项工作的另一个关键贡献是根据一些预定义的目标确定最佳检查时间集。本文介绍了基于多标准的最佳设计的确定。利用基于人群的启发式算法非主导分类的多物镜遗传算法来解决此优化问题。
Recently, a growing amount interest is quite evident in modelling dependent competing risks in life time prognosis problem. In this work, we propose to model the dependent competing risks by Marshal-Olkin bivariate exponential distribution. The observable data consists of number of failures due to different causes across different time intervals. The failure count data is common in instances like one shot devices where state of the subjects are inspected at different inspection times rather than the exact failure times. The point estimation of the life time distribution in presence of competing risk has been studied through divergence based robust estimation method called minimum density power divergence estimation (MDPDE). The testing of hypothesis is performed based on a Wald type test statistic. The influence function is derived both for the point estimator and the test statistic, which reflects the degree of robustness. Another, key contribution of this work is to determine the optimal set of inspection times based on some predefined objectives. This article presents determination of multi criteria based optimal design. Population based heuristic algorithm non-dominated sorting-based multiobjective Genetic algorithm is exploited to solve this optimization problem.
