Edgeworth approximation of multivariate differential entropy.
We develop the general, multivariate case of the Edgeworth approximation of differential entropy and show that it can be more accurate than the nearest-neighbor method in the multivariate case and that it scales better with sample size. Furthermore, we introduce mutual information estimation as an application.
Van Hulle
Marc M
MM
K. U. Leuven, Laboratorium voor Neuro- en Psychofysiologie, B-3000 Leuven, Belgium. marc@neuro.kuleuven.ac.be
D000465:Algorithms; D019277:Entropy; D016571:Neural Networks, Computer