Discrepancy is an important criterion for uniformity in the design of experiments. Basically, it measures the distance between two functions: the empirical distribution of the design points and the theoretical uniform distribution function. This paper studies the properties of uniformity when...

Latin hypercube designs have found wide application. Such designs guarantee uniform samples for the marginal distribution of each input variable. We propose a method for constructing orthogonal Latin hypercube designs in which all the linear terms are orthogonal not only to each other, but also...

Due to run size constraints, near-orthogonal arrays (near-OAs) and supersaturated designs, a special case of near-OA, are considered good alternatives to OAs. This paper shows (i) a combinatorial relationship between a mixed-level array and a non-resolvable incomplete block design (IBD) with...