Abstract
Non-regular factorial designs have not been advocated until last decade clue to their complex aliasing structure. However, some researchers recently found that the complex aliasing structure of non-regular factorial designs is a challenge as well as an opportunity. Li, Deng, and Tang (2000) studied nonl-regular designs and generated a collection of non-equivalent orthogonal arrays using a generalized miniumm aberration criterion, proposed by Deng and Tang (1999). Some new orthogonal arrays they found cannot be embedded into Hadamard matrices. In this paper, we study these orthogonal arrays from the angle of projection. We show that these new GMA orthogonal arrays are also superior to the top designs obtained from Hadamard matrices when evaluated hy the criteria of model estimability and design efficiency.
Keywords
non-regular design, generalized minimum aberration, model estimability, design efficiency, Hadamard matrices, orthogonal arrays
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Li, Yingfu and Wittig, Timothy
(2001).
"ANOTHER LOOK AT NEW GMA ORTHOGONAL ARRAYS,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1220
ANOTHER LOOK AT NEW GMA ORTHOGONAL ARRAYS
Non-regular factorial designs have not been advocated until last decade clue to their complex aliasing structure. However, some researchers recently found that the complex aliasing structure of non-regular factorial designs is a challenge as well as an opportunity. Li, Deng, and Tang (2000) studied nonl-regular designs and generated a collection of non-equivalent orthogonal arrays using a generalized miniumm aberration criterion, proposed by Deng and Tang (1999). Some new orthogonal arrays they found cannot be embedded into Hadamard matrices. In this paper, we study these orthogonal arrays from the angle of projection. We show that these new GMA orthogonal arrays are also superior to the top designs obtained from Hadamard matrices when evaluated hy the criteria of model estimability and design efficiency.
