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 $\hat{\mu}_n$ based on a Latin
hypercube sample. The second establishes sufficient conditions on the convergence rate in the strong law for $\hat{\mu}_n$. 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.
Publié le : 1996-10-14
Classification:
Berry-Esseen bound,
confidence regions,
Latin hypercube sampling,
multivariate central limit theorem,
Stein's method,
strong law of large numbers,
62D05,
62E20,
62G15
@article{1069362310,
author = {Loh, Wei-Liem},
title = {On Latin hypercube sampling},
journal = {Ann. Statist.},
volume = {24},
number = {6},
year = {1996},
pages = { 2058-2080},
language = {en},
url = {http://dml.mathdoc.fr/item/1069362310}
}
Loh, Wei-Liem. On Latin hypercube sampling. Ann. Statist., Tome 24 (1996) no. 6, pp. 2058-2080. http://gdmltest.u-ga.fr/item/1069362310/