On modelling data from degradation sample paths over time

Abstract

This paper is mainly concerned with modelling data from degradation sample paths over time. It uses a general growth curve model with Box-Cox transformation, random effects and ARMA(p, q) dependence to analyse a set of such data. A maximum likelihood estimation procedure for the proposed model is derived and future values are predicted, based on the best linear unbiased prediction. The paper compares the proposed model with a nonlinear degradation model from a prediction point of view. Forecasts of failure times with various data lengths in the sample are also compared.