Mathematical justifications are given for a Monte Carlo simulation technique based on memoryless transformations of Gaussian processes. Different types of convergences are given for the approaching sequence. Moreover an original numerical method is proposed in order to solve the functional equation yielding the underlying Gaussian process autocorrelation function.
Publié le : 2002-07-05
Classification:
hermite polynomial expansion,
non-Gaussian process,
uncertainty quantification,
Monte Carlo simulation,
[SPI.MECA]Engineering Sciences [physics]/Mechanics [physics.med-ph],
[MATH.MATH-PR]Mathematics [math]/Probability [math.PR],
[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]
@article{hal-00686282,
author = {Puig, B\'en\'edicte and Poirion, F. and Soize, Christian},
title = {Non-Gaussian simulation using Hermite polynomial expansion: convergences and algorithms},
journal = {HAL},
volume = {2002},
number = {0},
year = {2002},
language = {en},
url = {http://dml.mathdoc.fr/item/hal-00686282}
}
Puig, Bénédicte; Poirion, F.; Soize, Christian. Non-Gaussian simulation using Hermite polynomial expansion: convergences and algorithms. HAL, Tome 2002 (2002) no. 0, . http://gdmltest.u-ga.fr/item/hal-00686282/