Some results of error evaluation for a non-Gaussian simulation method

Akian Jean-Luc and Puig Bénédicte
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Akian Jean-Luc: ONERA, BP72 92322 Châtillon, France
Puig Bénédicte: Universite de Paris X-Nanterre, France

Monte Carlo Methods and Applications, 2004, vol. 10, issue 1, 51-68

Abstract: In a first part of the paper a simulation method for a strictly stationary non-Gaussian process with given one-dimensional marginal distribution (or N-first statistical moments) and autocorrelation function is recalled. This method was already widely treated in the articles [14] and [13]. The objective of the present paper is twofold: first, to simplify this method - if by Mehler formula it is possible to find an autocorrelation function yielding the target autocorrelation function, and second, analyze the difference between the given autocorrelation function and the model one.

Keywords: Monte-Carlo simulation; non-Gaussian process; Hermite polynomials; maximum entropy principle. (search for similar items in EconPapers)
Date: 2004
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DOI: 10.1515/156939604323091207

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