Computation of confidence regions for optimal factor levels in constrained response surface problems

Suntara Cahya; Enrique Del Castillo; John J. Peterson

doi:10.1198/1061860043443

Computation of confidence regions for optimal factor levels in constrained response surface problems

Suntara Cahya, Enrique Del Castillo, John J. Peterson

Research output: Contribution to journal › Article › peer-review

11 Scopus citations

Abstract

This article presents an improved approach for computing the confidence regions for the optimal factor settings obtained from optimizing a general response surface model. The approach has a better computational efficiency and improved accuracy compared to existing methodology. A three-factor mixture experiment was used for the performance comparison. The coverage rate properties of the resulting confidence regions were assessed through an extensive simulation study.

Original language	English (US)
Pages (from-to)	499-518
Number of pages	20
Journal	Journal of Computational and Graphical Statistics
Volume	13
Issue number	2
DOIs	https://doi.org/10.1198/1061860043443
State	Published - Jun 2004

All Science Journal Classification (ASJC) codes

Statistics and Probability
Discrete Mathematics and Combinatorics
Statistics, Probability and Uncertainty

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10.1198/1061860043443

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abstract = "This article presents an improved approach for computing the confidence regions for the optimal factor settings obtained from optimizing a general response surface model. The approach has a better computational efficiency and improved accuracy compared to existing methodology. A three-factor mixture experiment was used for the performance comparison. The coverage rate properties of the resulting confidence regions were assessed through an extensive simulation study.",

author = "Suntara Cahya and {Del Castillo}, Enrique and Peterson, {John J.}",

year = "2004",

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AU - Del Castillo, Enrique

AU - Peterson, John J.

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AB - This article presents an improved approach for computing the confidence regions for the optimal factor settings obtained from optimizing a general response surface model. The approach has a better computational efficiency and improved accuracy compared to existing methodology. A three-factor mixture experiment was used for the performance comparison. The coverage rate properties of the resulting confidence regions were assessed through an extensive simulation study.

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Computation of confidence regions for optimal factor levels in constrained response surface problems

Abstract

All Science Journal Classification (ASJC) codes

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