%0 Journal Article
%A Grassberger, Peter
%T On Generalized Schürmann Entropy Estimators
%J Entropy
%V 24
%N 5
%@ 1099-4300
%C Basel
%I MDPI
%M FZJ-2022-02887
%P 680 -
%D 2022
%X 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.
%F PUB:(DE-HGF)16
%9 Journal Article
%$ 35626564
%U <Go to ISI:>//WOS:000801648200001
%R 10.3390/e24050680
%U https://juser.fz-juelich.de/record/908873