当前位置: X-MOL 学术IEEE Trans. Reliab. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Robust Inference for One-Shot Device Testing Data Under Weibull Lifetime Model
IEEE Transactions on Reliability ( IF 5.9 ) Pub Date : 2020-09-01 , DOI: 10.1109/tr.2019.2954385
Narayanaswamy Balakrishnan , Elena Castilla , Nirian Martin , Leandro Pardo

Classical inferential methods for one-shot device testing data from an accelerated life-test are based on maximum likelihood estimators (MLEs) of model parameters. However, the lack of robustness of MLE is well-known. In this article, we develop robust estimators for one-shot device testing by assuming a Weibull distribution as a lifetime model. Wald-type tests based on these estimators are also developed. Their robustness properties are evaluated both theoretically and empirically, through an extensive simulation study. Finally, the methods of inference proposed are applied to three numerical examples. Results obtained from both Monte Carlo simulations and numerical studies show the proposed estimators to be a robust alternative to MLEs.

中文翻译:

威布尔寿命模型下一次性设备测试数据的鲁棒推理

来自加速寿命测试的一次性设备测试数据的经典推理方法基于模型参数的最大似然估计 (MLE)。然而,MLE 缺乏鲁棒性是众所周知的。在本文中,我们通过假设威布尔分布作为寿命模型来开发用于一次性设备测试的稳健估计器。还开发了基于这些估计量的 Wald 型测试。通过广泛的模拟研究,从理论上和经验上对它们的稳健性进行了评估。最后,将所提出的推理方法应用于三个数值例子。从 Monte Carlo 模拟和数值研究中获得的结果表明,所提出的估计器是 MLE 的可靠替代方案。
更新日期:2020-09-01
down
wechat
bug