Journal Article

FZJ-2022-02887

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png On Generalized Schürmann Entropy Estimators

Grassberger, P. (Corresponding author)FZJ*

2022
MDPI Basel

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Please use a persistent id in citations: http://hdl.handle.net/2128/31595  doi:10.3390/e24050680

Abstract: We present a new class of estimators of Shannon entropy for severely undersampleddiscrete distributions. It is based on a generalization of an estimator proposed by T. Schürmann,which itself is a generalization of an estimator proposed by myself.For a special set of parameters,they are completely free of bias and have a finite variance, something which is widely believedto be impossible. We present also detailed numerical tests, where we compare them with otherrecent estimators and with exact results, and point out a clash with Bayesian estimators for mutualinformation.

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Contributing Institute(s):

1. Jülich Supercomputing Center (JSC)

Research Program(s):

1. 5111 - Domain-Specific Simulation & Data Life Cycle Labs (SDLs) and Research Groups (POF4-511) (POF4-511)

Appears in the scientific report 2022

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