Bayesian Analysis of Variable-Stress Accelerated Life Testing

Richard Nii Okine, University of Texas at El Paso


Several authors have over the years studied the art of modeling data from accelerated life testing and making inferences from such data. In this study, we consider a continuously varying stress accelerated life testing procedure which is the limiting case of the multiple stress-level discussed by Doksum and H´oyland [1]. We derive the likelihood function for the life distribution of the continuously increasing stress accelerated life testing model and consequently the Fisher’s Information Matrix. We propose a Bayesian analysis for this distribution using the Gibbs Sampling Procedure. We conduct simulation studies and real data analysis to demonstrate the efficiency of the proposed Bayesian approach to parameter estimation over that of maximum likelihood estimation procedure.

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Recommended Citation

Okine, Richard Nii, "Bayesian Analysis of Variable-Stress Accelerated Life Testing" (2019). ETD Collection for University of Texas, El Paso. AAI27737113.