A sliced Latin hypercube design is a special Latin hypercube design that can be divided into slices of smaller Latin hypercube designs. This type of designs is useful for computer experiments with qualitative and quantitative factors, multiple experiments, data pooling, and cross-validation. Orthogonality and uniformity are important properties for Latin hypercube designs. In this paper, sliced maximin-orthogonal Latin hypercube designs are constructed using orthogonal designs, Goethals-Seidel arrays, and Kharaghani arrays. The resulting designs have both second-order orthogonality and good uniformity.
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Statistics, Probability and Uncertainty