The parallel constant-stress accelerated degradation test (PCSADT) is a popular method used to assess the reliability of highly reliable products in a timely manner. Although the maximum likelihood (ML) method is commonly utilized to estimate the PCSADT parameters, the explicit forms of the ML estimators, and their corresponding Fisher information matrix are usually difficult to obtain. In this article, we propose a two-stage ML (TSML) estimation procedure for a time-transformed model. In the proposed procedure, all the TSML estimators not only have explicit expressions but also possess consistency and asymptotic normality. Hence, this method is tractable for reliability engineers. Furthermore, the TSML estimators can provide constructive information about the unknown accelerated relationship law. The proposed method is also applied to analyze light-emitting diode data and compare the performance of our estimation procedures with the ML method via simulations.

中文翻译：

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并行恒定应力加速退化试验的两阶段最大似然估计程序

平行恒定应力加速退化试验 (PCSADT) 是一种流行的方法，用于及时评估高可靠性产品的可靠性。尽管通常使用最大似然 (ML) 方法来估计 PCSADT 参数，但通常难以获得 ML 估计量的显式形式及其相应的 Fisher 信息矩阵。在本文中，我们为时间转换模型提出了一个两阶段 ML (TSML) 估计程序。在所提出的过程中，所有 TSML 估计量不仅具有显式表达式，而且还具有一致性和渐近正态性。因此，这种方法对于可靠性工程师来说是易于处理的。此外，TSML 估计器可以提供有关未知加速关系定律的建设性信息。