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Optimizing two-level orthogonal arrays for simultaneously estimating main effects and pre-specified two-factor interactions
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Optimizing two-level orthogonal arrays for simultaneously estimating main effects and pre-specified two-factor interactions

Ping-Yang Chen, Ray-Bing ChenC. Devon Lin
Computational Statistics and Data Analysis, 卷.118, 頁碼.84-97
02/2018

摘要

D-optimal design Fractional factorial design Hadamard matrix Swarm intelligence optimization Statistics and Probability Computational Mathematics Computational Theory and Mathematics Applied Mathematics
This paper considers the construction of D-optimal two-level orthogonal arrays that allow for the joint estimation of all main effects and a specified set of two-factor interactions. A sharper upper bound on the determinant of the related matrix is derived. To numerically obtain D-optimal and nearly D-optimal orthogonal arrays of large run sizes, an efficient search procedure is proposed based on a discrete optimization algorithm. Results on designs of 20, 24, 28, 36, 44 and 52 runs with three or fewer two-factor interactions are illustrated here to demonstrate the performance of the proposed approach. In addition, two cases with four two-factor interactions are also demonstrated here.

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