Non-Gaussian process generation
Updated 28 Mar 2023
A non-Gaussian distribution is generated from a Gaussian-distributed white noise
The method used in these files is based on the Moment Based Hermite Transformation Model (MBHTM) and uses a cubic transformation to transform a Gaussian process into a non-Gaussian one. It is described in . However, I mainly rely on  for the implementation of the code. A target skewness and a target kurtosis are used to introduce non-Gaussianity. However, the transformation only works for a limited range of skewness and kurtosis. See  for more details.
Two files are included
MBHTM.m which is the main function to generare the non-Gaussian process
Documentation.mlx which is the example file
 Gurley, K. R., Tognarelli, M. A., & Kareem, A. (1997). Analysis and simulation tools for wind engineering. Probabilistic Engineering Mechanics, 12(1), 9-31.
 Denoël, V. (2005). Application des méthodes d'analyse stochastique à l’étude des effets du vent sur les structures du génie civil. Unpublished doctoral thesis, University of Liège. (in French, p. 229)
E. Cheynet (2023). Non-Gaussian process generation (https://github.com/ECheynet/Gaussian_to_nonGaussian/releases/tag/v1.2), GitHub. Retrieved .
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See release notes for this release on GitHub: https://github.com/ECheynet/Gaussian_to_nonGaussian/releases/tag/v1.2
See release notes for this release on GitHub: https://github.com/ECheynet/Gaussian_to_nonGaussian/releases/tag/v1.1