Introduced robust density‐based estimators in the context of one‐shot devices with exponential lifetimes under a single stress factor. However, it is usual to have several stress factors in industrial experiments involving one‐shot devices. In this paper, the weighted minimum density power divergence estimators (WMDPDEs) are developed as a natural extension of the classical maximum likelihood estimators (MLEs) for one‐shot device testing data under exponential lifetime model with multiple stresses. Based on these estimators, Wald‐type test statistics are also developed. Through a simulation study, it is shown that some WMDPDEs have a better performance than the MLE in relation to robustness. Two examples with multiple stresses show the usefulness of the model and, in particular, of the proposed estimators, both in engineering and medicine.

中文翻译：

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具有多重压力的指数寿命模型下的一次性测试数据的鲁棒推断

在具有单个应力因子的指数寿命的单次设备中引入了鲁棒的基于密度的估计器。但是，在涉及一次性设备的工业实验中，通常会遇到多个压力因素。本文将加权最小密度功率发散估计器（WMDPDE）作为经典最大似然估计器（MLE）的自然扩展，用于在多重应力下的指数寿命模型下的单次设备测试数据。基于这些估计量，还开发了Wald型检验统计量。通过仿真研究表明，在鲁棒性方面，某些WMDPDE具有比MLE更好的性能。带有多个应力的两个示例显示了该模型的实用性，特别是在工程和医学领域中所提出的估计器的实用性。