Accelerated life test (ALT) planning in Bayesian framework is studied in this paper with a focus of differentiating competing acceleration models, when there is uncertainty as to whether the relationship between log mean life and the stress variable is linear or exhibits some curvature. The proposed criterion is based on the Hellinger distance measure between predictive distributions.
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- Nasir, Ehab A. (Author)
- Pan, Rong (Author)
- Ira A. Fulton Schools of Engineering (Contributor)
- Digital object identifier: 10.1016/j.ress.2014.10.002
- Identifier TypeInternational standard serial numberIdentifier Value0951-8320
- NOTICE: this is the author's version of a work that was accepted for publication in RELIABILITY ENGINEERING & SYSTEM SAFETY. Changes resulting from the publishing process, such as editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in RELIABILITY ENGINEERING & SYSTEM SAFETY, 134, 1-9. DOI: 10.1016/j.ress.2014.10.002, opens in a new window
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Nasir, Ehab A., & Pan, Rong (2015). Simulation-based Bayesian optimal ALT designs for model discrimination. RELIABILITY ENGINEERING & SYSTEM SAFETY, 134, 1-9. http://dx.doi.org/10.1016/j.ress.2014.10.002