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Optimal Partitions for Nonparametric Multivariate Entropy Estimation
[article]
2023
arXiv
pre-print
Efficient and accurate estimation of multivariate empirical probability distributions is fundamental to the calculation of information-theoretic measures such as mutual information and transfer entropy. Common techniques include variations on histogram estimation which, whilst computationally efficient, are often unable to precisely capture the probability density of samples with high correlation, kurtosis or fine substructure, especially when sample sizes are small. Adaptive partitions, which
arXiv:2112.06299v2
fatcat:sxwixhnsyvbgxc72ndouyejici