${E(s^2)}$-Optimality and Minimum Discrepancy in 2-level Supersaturated Designs

Supersaturated experimental designs are often assessed by the E(s 2 )c ri- terion, and some methods have been found for constructing E(s 2 )-optimal designs. Another criterion for assessing experimental designs is discrepancy, of which there are several different kinds. The discrepancy measures how much the empirical distribution of the design points deviates from the uniform distribution. Here it is shown that for 2-level supersaturated designs the E(s 2 ) criterion and a certain discrepancy share the same optimal designs.

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