  Latin hypercube designs achieve optimal univariate stratifications and are
useful for computer experiments. Sliced Latin hypercube designs are Latin
hypercube designs that can be partitioned into smaller Latin hypercube designs.
In this work, we give, to the best of our knowledge, the first construction of
sliced Latin hypercube designs that allow arbitrarily chosen run sizes for the
slices. We also provide an algorithm to reduce correlations of our proposed
designs.
