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Nonparametric Estimation of Renyi Divergence and Friends

Abstract

We consider nonparametric estimation of L2L_2, Renyi-α\alpha and Tsallis-α\alpha divergences between continuous distributions. Our approach is to construct estimators for particular integral functionals of two densities and translate them into divergence estimators. For the integral functionals, our estimators are based on corrections of a preliminary plug-in estimator. We show that these estimators achieve the parametric convergence rate of n1/2n^{-1/2} when the densities' smoothness, ss, are both at least d/4d/4 where dd is the dimension. We also derive minimax lower bounds for this problem which confirm that s>d/4s > d/4 is necessary to achieve the n1/2n^{-1/2} rate of convergence. We validate our theoretical guarantees with a number of simulations.

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