Open Access
Translator Disclaimer
June 1996 A combinatorial central limit theorem for randomized orthogonal array sampling designs
Wei-Liem Loh
Ann. Statist. 24(3): 1209-1224 (June 1996). DOI: 10.1214/aos/1032526964

Abstract

Let X be a random vector uniformly distributed on the unit cube and $f: [0, 1]^3 \to \mathsf{R}$ be a measurable function. An objective of many computer experiments is to estimate $\mu = E(f \circ X)$ by computing f at a set of points in $[0, 1]^3$. There is a design issue in choosing these points. Recently Owen and Tang independently suggested using randomized orthogonal arrays in the choice of such a set. This paper investigates the convergence rate to normality of the distribution of the average of a set of f values taken from one of these designs.

Citation

Download Citation

Wei-Liem Loh. "A combinatorial central limit theorem for randomized orthogonal array sampling designs." Ann. Statist. 24 (3) 1209 - 1224, June 1996. https://doi.org/10.1214/aos/1032526964

Information

Published: June 1996
First available in Project Euclid: 20 September 2002

zbMATH: 0869.62018
MathSciNet: MR1401845
Digital Object Identifier: 10.1214/aos/1032526964

Subjects:
Primary: 62E20
Secondary: 60F05, 62D05

Rights: Copyright © 1996 Institute of Mathematical Statistics

JOURNAL ARTICLE
16 PAGES


SHARE
Vol.24 • No. 3 • June 1996
Back to Top