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Article

Keywords:
entropy; wavelet estimation; rate of convergence; mean $\mathbb{L}_p$ error
Summary:
In this note we consider the estimation of the differential entropy of a probability density function. We propose a new adaptive estimator based on a plug-in approach and wavelet methods. Under the mean $\mathbb{L}_p$ error, $p\ge 1$, this estimator attains fast rates of convergence for a wide class of functions. We present simulation results in order to support our theoretical findings.
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