While the Matrix Generalized Inverse Gaussian (MGIG) distribution arises naturally in some settings as a distribution over symmetric positive semi-definite matrices, certain key properties of the distribution and effective ways of sampling from the distribution have not been carefully studied. In this paper, we show that the MGIG is unimodal, and the mode can be obtained by solving an Algebraic...

Non-Gaussian distributions are commonly observed in collisionless space plasmas. Generating samples from non-Gaussian is critical for the initialization of particle-in-cell simulations that investigate their driven and undriven dynamics. To this end, we report a computationally efficient, robust tool, Chebsampling, to sample general distribution functions one two dimensions. This tool based on ...

In this paper we study algorithms to find a Gaussian approximation to a target measure defined on a Hilbert space of functions; the target measure itself is defined via its density with respect to a reference Gaussian measure. We employ the Kullback–Leibler divergence as a distance and find the best Gaussian approximation by minimizing this distance. It then follows that the approximate Gaussia...