The Inverse Gaussian Process as a Degradation Model
The Inverse Gaussian Process as a Degradation Model
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DOI：
10.1080/00401706.2013.830074
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发表时间：
2014-08-01
期刊：
影响因子：
2.5
通讯作者：
Chen, Nan
中科院分区：
文献类型：
--
作者：
Ye, Zhi-Sheng;Chen, Nan
本文系统地研究了逆高斯（IG）过程作为一种有效的退化模型。结果表明，IG过程是一种极限复合泊松过程，这使其在对随机环境中退化的产品进行退化建模时具有有意义的物理解释。将IG过程视为维纳过程的首达过程，它在纳入随机效应和解释变量方面具有灵活性，这些变量可解释退化问题中常见的异质性。与在退化建模文献中已被深入研究的伽马过程相比，这种灵活性使得IG过程模型类别更具吸引力。本文还讨论了三种随机效应模型的统计推断和模型选择。最后通过一个实际例子展示了IG过程在退化分析中的适用性。本文的补充材料可在线获取。
This article systematically investigates the inverse Gaussian (IG) process as an effective degradation model. The IG process is shown to be a limiting compound Poisson process, which gives it a meaningful physical interpretation for modeling degradation of products deteriorating in random environments. Treated as the first passage process of a Wiener process, the IG process is flexible in incorporating random effects and explanatory variables that account for heterogeneities commonly observed in degradation problems. This flexibility makes the class of IG process models much more attractive compared with the Gamma process, which has been thoroughly investigated in the literature of degradation modeling. The article also discusses statistical inference for three random effects models and model selection. It concludes with a real world example to demonstrate the applicability of the IG process in degradation analysis. Supplementary materials for this article are available online.