TY  - JOUR
AU  - Grassberger, Peter
TI  - On Generalized Schürmann Entropy Estimators
JO  - Entropy
VL  - 24
IS  - 5
SN  - 1099-4300
CY  - Basel
PB  - MDPI
M1  - FZJ-2022-02887
SP  - 680 -
PY  - 2022
AB  - 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.
LB  - PUB:(DE-HGF)16
C6  - 35626564
UR  - <Go to ISI:>//WOS:000801648200001
DO  - DOI:10.3390/e24050680
UR  - https://juser.fz-juelich.de/record/908873
ER  -