Non-Gaussian process generation

A non-Gaussian random process is generated from a Gaussian-distributed white noise

Gaussian_to_nonGaussian

A non-Gaussian distribution is generated from a Gaussian-distributed white noise

Summary

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 [1]. However, I mainly rely on [2] 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 [2] for more details.

Content

Two files are included

• MBHTM.m which is the main function to generare the non-Gaussian process

• Documentation.mlx which is the example file

References

[1] Gurley, K. R., Tognarelli, M. A., & Kareem, A. (1997). Analysis and simulation tools for wind engineering. Probabilistic Engineering Mechanics, 12(1), 9-31.

[2] 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 Unpublished doctoral thesis, University of Liège.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)