Refinement strategies for stratified sampling methods

  title={Refinement strategies for stratified sampling methods},
  author={Charles Tong},
  journal={Rel. Eng. & Sys. Safety},
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. Published by Elsevier Ltd. 


Publications referenced by this paper.
Showing 1-10 of 20 references

A method for extending the size of a latin hypercube sample

  • C. Sallaberry
  • Preprint, Sandia National Laboratories;
  • 2004
Highly Influential
2 Excerpts

Orthogonal array-based latin hypercubes

  • B. Tang
  • J Am Statist Assn 1993;88:1392–7
  • 1993
Highly Influential
3 Excerpts

Adaptive response surface method using inherited latin hypercube design points

  • GG Wang
  • Trans ASME, J Mech Designs
  • 2002

Orthogonal arrays: theory and applications. Springer series in statistics

  • AS Hedayat, NJa Sloane, J. Stufken
  • 1999
2 Excerpts

Similar Papers

Loading similar papers…