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- Title
Bayesian analysis for weighted mean-squared error in dual response surface optimization.
- Authors
In-Jun Jeong; Kwang-Jae Kim; Dennis K. J. Lin
- Abstract
Dual response surface optimization considers the mean and the variation simultaneously. The minimization of mean-squared error (MSE) is an effective approach in dual response surface optimization. Weighted MSE (WMSE) is formed by imposing the relative weights, (λ, 1-λ), on the squared bias and variance components of MSE. To date, a few methods have been proposed for determining λ. The resulting λ from these methods is either a single value or an interval. This paper aims at developing a systematic method to choose a λ value when an interval of λ is given. Specifically, this paper proposes a Bayesian approach to construct a probability distribution of λ. Once the distribution of λ is constructed, the expected value of λ can be used to form WMSE. Copyright © 2009 John Wiley & Sons, Ltd.
- Subjects
BAYESIAN analysis; EXPERIMENTAL design; STRUCTURAL optimization; MATHEMATICAL optimization; DISTRIBUTION (Probability theory)
- Publication
Quality & Reliability Engineering International, 2010, Vol 26, Issue 5, p417
- ISSN
0748-8017
- Publication type
Article
- DOI
10.1002/qre.1058