Journal ArticleDOI
A new loss function-based method for multiresponse optimization
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The proposed method introduces predicted future responses in a loss function, which accommodates robustness and quality of predictions as well as bias in a single framework to give more reasonable results than the existing methods.Abstract:
A new method for multiresponse optimization is proposed that accommodates robustness, quality of prediction, and bias into a single framework by including predicted future responses in a loss function. Two examples demonstrate that the method gives more..read more
Citations
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Desirability function approach: A review and performance evaluation in adverse conditions
TL;DR: Results show that a less sophisticated desirability-based method can compete with other methods designed to perform well under adverse conditions and that the optimization measures justify its use in real life problems.
Journal ArticleDOI
An interactive desirability function method to multiresponse optimization
In-Jun Jeong,Kwang-Jae Kim +1 more
TL;DR: This paper proposes an interactive method based on the desirability function approach to facilitate the preference articulation process that would be highly effective in generating a compromise solution that is faithful to the DM's preference structure.
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A general framework for multiresponse optimization problems based on goal programming
TL;DR: This study proposes a general framework in MRS problems according to some existing works and some types of related decision makers and attempts to aggregate all of characteristics in one approach.
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A desirability function method for optimizing mean and variability of multiple responses using a posterior preference articulation approach
Journal ArticleDOI
A Bayesian Reliability Approach to Multiple Response Optimization with Seemingly Unrelated Regression Models
TL;DR: In this article, a Bayesian predictive approach to multiresponse optimization experiments is presented, which generalizes the work of Peterson [33] in two ways that make it more flexible for use in applications.
References
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Book
Applied Linear Statistical Models
TL;DR: Applied Linear Statistical Models 5e as discussed by the authors is the leading authoritative text and reference on statistical modeling, which includes brief introductory and review material, and then proceeds through regression and modeling for the first half, and through ANOVA and Experimental Design in the second half.
Journal ArticleDOI
Applied Linear Statistical Models
Journal ArticleDOI
An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias
TL;DR: In this paper, a method of estimating the parameters of a set of regression equations is reported which involves application of Aitken's generalized least-squares to the whole system of equations.
Journal ArticleDOI
Simultaneous Optimization of Several Response Variables
TL;DR: In this article, the authors present a set of conditions that will result in a product with a desirable combination of properties, which is a problem facing the product development community in general.
Book
Quality Engineering in Production Systems
TL;DR: In this article, the quality engineering in production systems (QESIS) has been studied for the first time in the context of a large scale production system with a large number of components.