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Linear Bayesian Inference for Accelerated Weibull Model |
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| Authors: | Mazzuchi Thomas A. Soyer Refik Vopatek Anne L. |
| Affiliation: | (1) Department of Operations Research and Department of Engineering Management, The George Washington University, Washington, D.C, 20052;(2) Department of Management Science, The George Washington University, Washington, D.C, 20052;(3) Head Quarters DNA, US Department of Defense, Alexandria, VA, 22310 |
| Abstract: | In this paper, we present a Bayesian approach for inference from accelerated life tests when the underlying life model is Weibull. Our approach is based on the General Linear Models framework of West, Harrison and Migon (1985). We discuss inference for the model and show that computable results can be obtained using linear Bayesian methods. We illustrate the usefulness of our approach by applying it to some actual data from accelerated life tests. This revised version was published online in July 2006 with corrections to the Cover Date. |
| Keywords: | Life testing Environmental testing General linear models Predictive inference |
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