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arxiv: 1602.07440 · v1 · pith:BDE6ZH6Gnew · submitted 2016-02-24 · 🧮 math.ST · stat.TH

On the Kozachenko-Leonenko entropy estimator

classification 🧮 math.ST stat.TH
keywords estimatorbiascentraldimensionsentropylimitsometheorem
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We study in details the bias and variance of the entropy estimator proposed by Kozachenko and Leonenko for a large class of densities on $\mathbb{R}^d$. We then use the work of Bickel and Breiman to prove a central limit theorem in dimensions $1$ and $2$. In higher dimensions, we provide a development of the bias in terms of powers of $N^{-2/d}$. This allows us to use a Richardson extrapolation to build, in any dimension, an estimator satisfying a central limit theorem and for which we can give some some explicit (asymptotic) confidence intervals.

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