Minimum Relative Entropy Inference for Normal and Monte Carlo Distributions

07/13/2020

∙

by   Marcello Colasante, et al.

∙

0

∙

share

We represent affine sub-manifolds of exponential family distributions as minimum relative entropy sub-manifolds. With such representation we derive analytical formulas for the inference from partial information on expectations and covariances of multivariate normal distributions; and we improve the numerical implementation via Monte Carlo simulations for the inference from partial information of generalized expectation type.