Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data
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, H...
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Online Access: | https://doi.org/10.1515/auoc-2017-0006 |
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doaj-5dd50b2dbfa9494e98a57476a97af3c82021-09-06T19:40:17ZengSciendoAnalele Universităţii "Ovidius" Constanţa: Seria Chimie2286-038X2017-08-01282304210.1515/auoc-2017-0006auoc-2017-0006Performances of Shannon’s Entropy Statistic in Assessment of Distribution of DataJäntschi Lorentz0Bolboacă Sorana D.1Technical University of Cluj-Napoca, Department of Physics and Chemistry, Muncii Blvd., No. 103-105, 400641 Cluj-Napoca, RomaniaIuliu Haţieganu University of Medicine and Pharmacy, Department of Medical Informatics and Biostatistics, Louis Pasteur Street, No. 6, 400349 Cluj-Napoca, RomaniaStatistical 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.https://doi.org/10.1515/auoc-2017-0006shannon’s entropystatisticcontinuous distributiontests of goodness-of-fit |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jäntschi Lorentz Bolboacă Sorana D. |
spellingShingle |
Jäntschi Lorentz Bolboacă Sorana D. Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data Analele Universităţii "Ovidius" Constanţa: Seria Chimie shannon’s entropy statistic continuous distribution tests of goodness-of-fit |
author_facet |
Jäntschi Lorentz Bolboacă Sorana D. |
author_sort |
Jäntschi Lorentz |
title |
Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data |
title_short |
Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data |
title_full |
Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data |
title_fullStr |
Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data |
title_full_unstemmed |
Performances of Shannon’s Entropy Statistic in Assessment of Distribution of Data |
title_sort |
performances of shannon’s entropy statistic in assessment of distribution of data |
publisher |
Sciendo |
series |
Analele Universităţii "Ovidius" Constanţa: Seria Chimie |
issn |
2286-038X |
publishDate |
2017-08-01 |
description |
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. |
topic |
shannon’s entropy statistic continuous distribution tests of goodness-of-fit |
url |
https://doi.org/10.1515/auoc-2017-0006 |
work_keys_str_mv |
AT jantschilorentz performancesofshannonsentropystatisticinassessmentofdistributionofdata AT bolboacasoranad performancesofshannonsentropystatisticinassessmentofdistributionofdata |
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1717768894883561472 |