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- Title
Augmented probability simulation for accelerated life test design.
- Authors
Polson, Nicholas G.; Soyer, Refik
- Abstract
Designing accelerated life tests presents a number of conceptual and computational challenges. We propose a Bayesian decision-theoretic approach for selecting an optimal stress-testing schedule and develop an augmented probability simulation approach to obtain the optimal design. The notion of a 'dual utility probability density' enables us to invoke the concept of a conjugate utility function. For accelerated life tests, this allows us to construct an augmented probability simulation that simultaneously optimizes and calculates the expected utility. In doing so, we circumvent many of the computational difficulties associated with evaluating pre-posterior expected utilities. To illustrate our methodology, we consider a single-stage accelerated life test design; our approach naturally extends to multiple-stage designs. Finally, we conclude with suggestions for further research. Copyright © 2017 John Wiley & Sons, Ltd.
- Subjects
PROBABILITY theory; ACCELERATED life testing; PARTICLE methods (Numerical analysis); MATHEMATICAL optimization; SIMULATION methods &; models
- Publication
Applied Stochastic Models in Business & Industry, 2017, Vol 33, Issue 3, p322
- ISSN
1524-1904
- Publication type
Article
- DOI
10.1002/asmb.2256