Estimating differential entropy using recursive copula split

Version 1.0.3 (4,12 ko) par Gil Ariel
An algorithm for estimating the entropy of a continuous random variable. Uses recursive splitting of the copula.
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Mise à jour 6 jan. 2022

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A method for estimating the Shannon differential entropy of multidimensional random variables using independent samples. The method is based on decomposing the distribution into a product of the marginal distributions and the joint dependency, also known as the copula. The entropy of marginals is estimated using one-dimensional methods.The entropy of the copula, which always has a compact support, is estimated recursively by splitting the data along statistically dependent dimensions.
The method can be applied both for distributions with compact and non-compact support. See Ariel and Louzoun, arXiv:1911.06204 for details.

Citation pour cette source

Gil Ariel (2024). Estimating differential entropy using recursive copula split (https://www.mathworks.com/matlabcentral/fileexchange/74219-estimating-differential-entropy-using-recursive-copula-split), MATLAB Central File Exchange. Récupéré le .

Entropy 2020, 22(2), 236; https://doi.org/10.3390/e22020236

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Version Publié le Notes de version
1.0.3

Added correction term to 1D spacing estimation
1.0.2

Corrected missing file
1.0.1

Updated citation
1.0.0