On the consistency of the Kozachenko-Leonenko entropy estimate

preprint2021arXivOpen access

Abstract

We revisit the problem of the estimation of the differential entropy H(f)H(f) of a random vector XX in RdR^d with density ff, assuming that H(f)H(f) exists and is finite. In this note, we study the consistency of the popular nearest neighbor estimate HnH_n of Kozachenko and Leonenko. Without any smoothness condition we show that the estimate is consistent (E{∣Hn−H(f)∣}→0E\{|H_n - H(f)|\} \to 0 as n→∞n \to \infty) if and only if E{log⁡(∥X∥+1)}<∞\mathbb{E} \{ \log ( \| X \| + 1 )\} < \infty. Furthermore, if XX has compact support, then Hn→H(f)H_n \to H(f) almost surely.

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