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Optimal scaling of two-level factorial experiments

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  • Toman, Blaza

Abstract

The relationship of a response variable with k continuous explanatory variables can be effectively studied by imbedding a 2k factorial design in the k space. A Bayesian model enables us to use prior information to select the scale of the experiment design. In this paper, the experimental design is scaled according to a criterion based on the Shannon entropy and on a criterion based on the maximum posterior variance within the experimental region. The designs are optimal if the observations are made without error, as in computer experiments, and are approximately optimal in the setting where experimental error is possible, and the ratio of error variance to prior variance is small.

Suggested Citation

  • Toman, Blaza, 1993. "Optimal scaling of two-level factorial experiments," Statistics & Probability Letters, Elsevier, vol. 16(4), pages 331-336, March.
    • Handle: RePEc:eee:stapro:v:16:y:1993:i:4:p:331-336
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