Abstract
Much information is available about the construction and evaluation of the prediction variance properties of response surface designs for fitting a second-order model in a spherical region of interest. There is less information available about the prediction variance properties of second-order designs for a cuboidal region. In this paper, we construct and evaluate designs that are appropriate for the second-order model in cuboidal regions of interest. Several standard experimental designs are investigated and some new designs created using the G and I optimality criteria. We evaluate the designs using the variance of the predicted response over the design region. Variance dispersion graphs and fraction of design space plots are utilized to characterize the scaled prediction variance properties of the most promising designs.
Original language | English (US) |
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Pages (from-to) | 253-266 |
Number of pages | 14 |
Journal | Journal of Quality Technology |
Volume | 37 |
Issue number | 4 |
DOIs | |
State | Published - Oct 2005 |
Keywords
- Cuboidal Regions
- Genetic Algorithms
- Prediction Variance
- Response Surface Methodology
- Scaled Prediction Variance
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Strategy and Management
- Management Science and Operations Research
- Industrial and Manufacturing Engineering