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Collision Entropy Estimation in a One-Line Formula
Version 1
: Received: 18 May 2023 / Approved: 19 May 2023 / Online: 19 May 2023 (11:19:36 CEST)
Version 2 : Received: 23 May 2023 / Approved: 24 May 2023 / Online: 24 May 2023 (04:45:46 CEST)
Version 2 : Received: 23 May 2023 / Approved: 24 May 2023 / Online: 24 May 2023 (04:45:46 CEST)
How to cite: Gecchele, A. Collision Entropy Estimation in a One-Line Formula. Preprints 2023, 2023051438. https://doi.org/10.20944/preprints202305.1438.v1 Gecchele, A. Collision Entropy Estimation in a One-Line Formula. Preprints 2023, 2023051438. https://doi.org/10.20944/preprints202305.1438.v1
Abstract
Integer-order Rényi entropies are synthetic indices useful for the characterization of probability distributions. In recent decades, numerous studies have been conducted to arrive at unbiased and consistent estimates of these indices starting from experimental data, to derive a suitable classification method for the underlying processes. However, optimal solutions have not been reached yet. A one-line formula limited to the estimation of collision entropy is presented here. The results of some specific Monte Carlo experiments gave evidence of its validity even for the very low densities of the data spread in the sample space. The strengths of this method are efficiency, unbiased consistency, and generality.
Keywords
Rényi entropies; collision entropy estimation; collision entropy rate estimation
Subject
Physical Sciences, Mathematical Physics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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