Refinement strategies for stratified sampling methods

In many computer experiments the adequacy of a given sample to give acceptable statistical estimates cannot be determined a priori, and thus the ability to extend or refine an experimental design may be important. This paper describes refinement strategies for the class of stratified experimental designs such as latin hypercubes, orthogonal arrays, and factorial designs. A few applications are given to demonstrate their usefulness.