title: Edgeworth-expanded gaussian mixture density modeling.
abstract: Instead of increasing the order of the Edgeworth expansion of a single gaussian kernel, we suggest using mixtures of Edgeworth-expanded gaussian kernels of moderate order. We introduce a simple closed-form solution for estimating the kernel parameters based on weighted moment matching. Furthermore, we formulate the extension to the multivariate case, which is not always feasible with algebraic density approximation procedures.
authors.affiliation: K.U. Leuven, Laboratorium voor Neuro-en Psychofysiologie, Belgium. marc@neuro.kuleuven.ac.be
authors.forename: Marc M
authors.initials: MM
authors.lastname: Van Hulle
mesh_terms: D000465:Algorithms; D006801:Humans; D008959:Models, Neurological; D016571:Neural Networks, Computer; D016011:Normal Distribution