Non-Gaussian simulation using Hermite polynomials expansion and maximum entropy principle

The non-Gaussian simulation method using Hermite polynomials expansion presented in a previous article is improved. It is aimed to simulate the paths of a strictly stationary non-Gaussian process given the N-first moments of its one-dimensional marginal distribution and its autocorrelation function. The present new model consists in using the maximum entropy principle in order to determine its marginal distribution. This allows to obtain new results of convergence. The convergences of this new model are then examined and the method is illustrated by some examples.