Factor selection in screening experiments by aggregation over random models. (arXiv:2205.13497v1 [stat.ME])

Screening experiments are useful for screening out a small number of truly
important factors from a large number of potentially important factors. The
Gauss-Dantzig Selector (GDS) is often the preferred analysis method for
screening experiments. Just considering main-effects models can result in
erroneous conclusions, but including interaction terms, even if restricted to
two-factor interactions, increases the number of model terms dramatically and
challenges the GDS analysis. We propose a new analysis method, called
Gauss-Dantzig Selector Aggregation over Random Models (GDS-ARM), …

aggregation arxiv random