Exclusive Content & Downloads from ASQ

Using Orthogonal Arrays in the Sensitivity Analysis of Computer Models

Summary: ´╗┐[This abstract is based on the authors' abstract.] Permuted column sampling plans that are popular in sensitivity analysis of computer models are examined. Theses plans support estimation of first-order sensitivity coefficients, but estimates are biased when random column permutation is used to construct the sampling arrays. Deterministic column permutations may be used to eliminate this estimation bias. It is shown that any permuted column sampling plan that eliminates estimation bias can be characterized by an orthogonal array of strength 2. Approximate standard errors of the first-order sensitivity indices are given for this sampling plan, which is demonstrated with two examples.

Anyone with a subscription, including Site and Enterprise members, can access this article.

Other Ways to Access content:

Join ASQ

Join ASQ as a Full member. Enjoy all the ASQ member benefits including access to many online articles.

  • Topics: Sampling
  • Keywords: Computer programs, Design of experiments (DOE), Variance components, First order design, Uncertainty, Sampling plans, Orthogonal array (OA)
  • Author: Morris, Max D.; Moore, Leslie M.; McKay, Michael D.
  • Journal: Technometrics