Simulation techniques for generalized Gaussian densities
This contribution deals with the Monte Carlo simulation of generalized Gaussian random variables. Such a parametric family of distributions has been proposed in many applications in science to describe physical phenomena and in engineering, and it seems to be also useful in modelling economic and financial data. For values of the shape parameter alpha within a certain range, the distribution presents heavy tails. In particular, the cases alpha = 1/3 and alpha = 1/2 are considered. For such values of the shape parameter, different simulation methods are assessed.
generalized gaussian density monte carlo simulation heavy tails transformations of random variables lambert w function