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Department of Statistics, UCLA

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Moment Aberration Projection for Nonregular Fractional Factorial Designs


Nonregular fractional factorial designs such as Plackett-Burman designs are widely used in industrial experiments for run size economy and flexibility. A novel criterion, called moment aberration pro jection, is proposed to rank and classify nonregular designs. It measures the goodness of a design through moments of the number of coincidences between the rows of its pro jection designs. The new criterion is applied to rank and classify designs of 16, 20 and 27 runs. Examples are given to illustrate that the ranking of designs is supported by other design criteria.

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