2008/04/28 by Juan A. Bonachela, Juan A Bonachela, Haye Hinrichsen +2 · 3 citations
Biochemistry, Genetics and Molecular Biology · Mathematics · Physics and Astronomy · #Fractal and DNA sequence analysis #Statistical Distribution Estimation and Applications #Statistical Mechanics and Entropy #cond-mat.stat-mech #q-bio.QM
paper · pdf · doi:10.1088/1751-8113/41/20/202001
published as J. Phys. A: Math. Theor. 41 (2008) 202001 · 11 pages, 2 figures
openalex publication_date 2008/04/28 · arxiv created 2008/04/29 · arxiv updated 2009/12/01 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
Estimating entropies from limited data series is known to be a non-trivial task. Naive estimations are plagued with both systematic (bias) and statistical errors. Here, we present a new 'balanced estimator' for entropy functionals Shannon, R'enyi and Tsallis) specially devised to provide a compromise between low bias and small statistical errors, for short data series. This new estimator out-performs other currently available ones when the data sets are small and the probabilities of the possible outputs of the random variable are not close to zero. Otherwise, other well-known estimators remain a better choice. The potential range of applicability of this estimator is quite broad specially for biological and digital data series.