Please use this identifier to cite or link to this item: https://doi.org/10.1214/07-AOS530
Title: A multivariate central limit theorem for randomized orthogonal array sampling designs in computer experiments
Authors: Loh, W.-L. 
Keywords: Computer experiment
Multivariate central limit theorem
Numerical integration
OA-based latin hypercube
Randomized orthogonal array
Stein's method
Issue Date: Aug-2008
Citation: Loh, W.-L. (2008-08). A multivariate central limit theorem for randomized orthogonal array sampling designs in computer experiments. Annals of Statistics 36 (4) : 1983-2023. ScholarBank@NUS Repository. https://doi.org/10.1214/07-AOS530
Abstract: Let f : [0, 1)d → ℝ be an integrable function. An objective of many computer experiments is to estimate ∫[0, 1)d f(x)dx by evaluating f at a finite number of points in [0,1)d. There is a design issue in the choice of these points and a popular choice is via the use of randomized orthogonal arrays. This article proves a multivariate central limit theorem for a class of randomized orthogonal array sampling designs [Owen Statist. Sinica 2 (1992a) 439-452] as well as for a class of OA-based Latin hypercubes [Tang J. Amer. Statist. Assoc. 81 (1993) 1392-1397]. © Institute of Mathematical Statistics, 2008.
Source Title: Annals of Statistics
URI: http://scholarbank.nus.edu.sg/handle/10635/104945
ISSN: 00905364
DOI: 10.1214/07-AOS530
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