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Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data Cover

Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data

Open Access
|Sep 2017

Abstract

Statistical analysis starts with the assessment of the distribution of experimental data. Different statistics are used to test the null hypothesis (H0) stated as Data follow a certain/specified distribution. In this paper, a new test based on Shannon’s entropy (called Shannon’s entropy statistic, H1) is introduced as goodness-of-fit test. The performance of the Shannon’s entropy statistic was tested on simulated and/or experimental data with uniform and respectively four continuous distributions (as error function, generalized extreme value, lognormal, and normal). The experimental data used in the assessment were properties or activities of active chemical compounds. Five known goodness-of-fit tests namely Anderson-Darling, Kolmogorov-Smirnov, Cramér-von Mises, Kuiper V, and Watson U2 were used to accompany and assess the performances of H1.

DOI: https://doi.org/10.1515/auoc-2017-0006 | Journal eISSN: 2286-038X | Journal ISSN: 1583-2430
Language: English
Page range: 30 - 42
Submitted on: Jun 13, 2017
Accepted on: Jul 26, 2017
Published on: Sep 20, 2017
Published by: Ovidius University of Constanta
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
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© 2017 Lorentz Jäntschi, Sorana D. Bolboacă, published by Ovidius University of Constanta
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.