We present sharp bounds on the minimal errors of linear estimators for multivariate integration and $L_2$-approximation. This is done for a random field whose covariance kernel is a tensor product of one-dimensional kernels that satisfy the Sacks-Ylvisaker regularity conditions.
Publié le : 1995-05-14
Classification:
Multivariate stochastic processes,
integration,
approximation,
optimal linear estimators,
41A50,
41A55,
41A63,
62H12,
62G05
@article{1177004776,
author = {Ritter, Klaus and Wasilkowski, Grzegorz W. and Wozniakowski, Henryk},
title = {Multivariate Integration and Approximation for Random Fields Satisfying Sacks-Ylvisaker Conditions},
journal = {Ann. Appl. Probab.},
volume = {5},
number = {4},
year = {1995},
pages = { 518-540},
language = {en},
url = {http://dml.mathdoc.fr/item/1177004776}
}
Ritter, Klaus; Wasilkowski, Grzegorz W.; Wozniakowski, Henryk. Multivariate Integration and Approximation for Random Fields Satisfying Sacks-Ylvisaker Conditions. Ann. Appl. Probab., Tome 5 (1995) no. 4, pp. 518-540. http://gdmltest.u-ga.fr/item/1177004776/