This article considers the estimation of structured correlation
matrices in infinitely differentiable Gaussian random field models.The problem
is essentially motivated by the stochastic modeling of smooth deterministic
responses in computer experiments.In particular, the log-likelihood function is
determined explicitly in closed-form and the sieve maximum likelihood
estimators are shown to be strongly consistent under mild conditions.
Publié le : 2000-05-14
Classification:
Computer experiment,
sieve maximum likelihood estimation,
smooth Gaussian random field,
strong consistency,
structured correlation matrix,
62D05,
62E20,
62G15
@article{1015952003,
author = {Loh, Wei-Liem and Lam, Tao-Kai},
title = {Estimating structured correlation matrices in smooth Gaussian
random field models},
journal = {Ann. Statist.},
volume = {28},
number = {3},
year = {2000},
pages = { 880-904},
language = {en},
url = {http://dml.mathdoc.fr/item/1015952003}
}
Loh, Wei-Liem; Lam, Tao-Kai. Estimating structured correlation matrices in smooth Gaussian
random field models. Ann. Statist., Tome 28 (2000) no. 3, pp. 880-904. http://gdmltest.u-ga.fr/item/1015952003/