Please use this identifier to cite or link to this item: https://doi.org/10.1214/aos/1069362310
Title: On latin hypercube sampling
Authors: Loh, W.-L. 
Keywords: Berry-Esseen bound
Confidence regions
Latin hypercube sampling
Multivariate central limit theorem
Stein's method
Strong law of large numbers
Issue Date: Oct-1996
Citation: Loh, W.-L. (1996-10). On latin hypercube sampling. Annals of Statistics 24 (5) : 2058-2080. ScholarBank@NUS Repository. https://doi.org/10.1214/aos/1069362310
Abstract: This paper contains a collection of results on Latin hypercube sampling. The first result is a Berry-Esseen-type bound for the multivariate central limit theorem of the sample mean μ̂n based on a Latin hypercube sample. The second establishes sufficient conditions on the convergence rate in the strong law for μ̂n Finally motivated by the concept of empirical likelihood, a way of constructing nonparametric confidence regions based on Latin hypercube samples is proposed for vector means.
Source Title: Annals of Statistics
URI: http://scholarbank.nus.edu.sg/handle/10635/103720
ISSN: 00905364
DOI: 10.1214/aos/1069362310
Appears in Collections:Staff Publications

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