Factorial hypercube designs for spatial correlation regression

Raviprakash Salagame and Russell Barton

Journal of Applied Statistics, 1997, vol. 24, issue 4, 453-474

Abstract: The problem of generating a good experimental design for spatial correlation regression is studied in this paper. The quality of fit generated by random designs, Latin hypercube designs and factorial designs is studied for a particular response surface that arises in inkjet printhead design. These studies indicate that the quality of fit generated by spatial correlation models is highly dependent on the choice of design. A design strategy that we call 'factorial hypercubes' is introduced as a new method. This method can be thought of as an example of a more general class of hybrid designs. The quality of fit generated by these designs is compared with those of other methods. These comparisons indicate a better fit and less numerical problems with factorial hypercubes.

Date: 1997
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DOI: 10.1080/02664769723648

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