Student-t Processes for Degradation Analysis
- May 2020
- Volume 62 Issue 2
- pp. 223-235
- Peng, Chien-Yu, Cheng, Ya-Shan
The copyright of this article is not held by ASQ.
Stochastic processes are widely used to analyze degradation data, and the Gaussian process is a particularly common one. In this article, we propose a robust statistical model using a Student-t process to assess the lifetime information of highly reliable products. This model is statistically plausible and demonstrates a substantially improved fit when applied to real data. A computationally accurate approach is proposed to calculate the first-passage-time density function of the Student-t degradation-based process; related properties are investigated as well. In addition, this article provides parameter estimation using the EM-type algorithm and a simple model-checking procedure to evaluate the appropriateness of the model assumptions. Several case studies are performed to demonstrate the flexibility and applicability of the proposed model with random effects and explanatory variables.*Supplemental material accessed online through Taylor & Francis.