U-type designs and orthogonal Latin hypercube designs (OLHDs) have been used extensively for performing computer experiments. Both have good spaced filling properties in one-dimension. U-type designs may not have low correlations among the main effects, quadratic effects and two-factor...

A supersaturated design (SSD) is a design whose run size is not enough for estimating all the main effects. An important goal in the analysis of such designs is to identify active effects based on the effect sparsity assumption. A Bayesian variable selection strategy which combines the...

Supersaturated design (SSD) has received much interest because of its potential in factor screening experiments. Most studies focused mainly on balanced designs. This paper considers SSDs with general run sizes. The lower bounds of the [chi]2 proposed by [Yamada, S., Lin, D.K.J., 1999....