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On modelling data from degradation sample paths over time

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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.
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Keywords: ARMA(p, q) dependence; Box-Cox transformation; ECME; maximum likelihood estimation; semi-variogram

Document Type: Research Article

Affiliations: National Chiao Tung University

Publication date: September 1, 2003

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