Optimal and orthogonal Latin hypercube designs for computer experiments

Latin hypercube designs are often used in computer experiments as they ensure that few design points are redundant when there is effect sparsity. In this paper, designs suitable for factor screening are presented and they are shown to be efficient in terms of runs required per factor as well as having optimal and orthogonal properties. Designs orthogonal under full second‐order models are also constructed.