Analyzing degradation data with a random effects spline regression model

ABSTRACT

This article proposes using a random effects spline regression model to analyze degradation data. Spline regression avoids having to specify a parametric function for the true degradation of an item. A distribution for the spline regression coefficients captures the variation of the true degradation curves from item to item. We illustrate the proposed methodology with a real example using a Bayesian approach. The Bayesian approach allows prediction of degradation of a population over time and estimation of reliability is easy to perform.

KEYWORDS:

• basis
• Bayesian inference
• natural cubic spline
• prediction
• reliability

Acknowledgments

We thank C. C. Essix for her support and encouragement of this work. We also thank two anonymous referees whose insightful comments helped to improve this article.