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Universal Approximation on the Hypersphere (2004.06328v1)

Published 14 Apr 2020 in math.ST, stat.ME, and stat.TH

Abstract: It is well known that any continuous probability density function on $\mathbb{R}m$ can be approximated arbitrarily well by a finite mixture of normal distributions, provided that the number of mixture components is sufficiently large. The von-Mises-Fisher distribution, defined on the unit hypersphere $Sm$ in $\mathbb{R}{m+1}$, has properties that are analogous to those of the multivariate normal on $\mathbb{R}{m+1}$. We prove that any continuous probability density function on $Sm$ can be approximated to arbitrary degrees of accuracy by a finite mixture of von-Mises-Fisher distributions.

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