| Summary: | 碩士 === 國立臺灣師範大學 === 數學系 === 105 === In recent years, there are many scholars interested in experimental designs of a large number of factors, but such experiments may only have a few really important factors.
It is detrimental to cost control if we using full factorial designs or traditional fractional factorial designs to construct these experiments, so we could consider using supersaturated designs in this situation to do factor screening.
In this article, we first discuss the design matrix construction methods of supersaturated designs, including the split-half method and the interaction method proposed by Lin and Wu, and then compare with them. Next, we introduce forward stepwise selection, LASSO and Dantzig selector as three factor selection methods of supersaturated designs. Finally, we compare the three factor selection methods of supersaturated designs by important factor selection ratio under different simulation conditions, and applied it to real examples.
|
|---|
