Application of the entropic coefficient for interval number optimization during interval assessment

In solving many statistical problems, the most precise choice of the distribution law of a random variable is required, the sample of which the authors observe. This choice requires the construction of an interval series. Therefore, the problem arises of assigning an optimal number of intervals, and...

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Main Author: Tynynyka A. N.
Format: Article
Language:English
Published: Politehperiodika 2017-06-01
Series:Tekhnologiya i Konstruirovanie v Elektronnoi Apparature
Subjects:
Online Access:http://www.tkea.com.ua/tkea/2017/3_2017/pdf/08.pdf
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spelling doaj-1164a15e9454423f8d6c5d78e349d9992020-11-24T23:51:21ZengPolitehperiodikaTekhnologiya i Konstruirovanie v Elektronnoi Apparature2225-58182309-99922017-06-013495410.15222/TKEA2017.3.49Application of the entropic coefficient for interval number optimization during interval assessmentTynynyka A. N. 0Ukraine, Kyiv, KPI them.Igor SikorskyIn solving many statistical problems, the most precise choice of the distribution law of a random variable is required, the sample of which the authors observe. This choice requires the construction of an interval series. Therefore, the problem arises of assigning an optimal number of intervals, and this study proposes a number of formulas for solving it. Which of these formulas solves the problem more accurately? In [9], this question is investigated using the Pearson criterion. This article describes the procedure and on its basis gives formulas available in literature and proposed new formulas using the entropy coefficient. A comparison is made with the previously published results of applying Pearson's concord criterion for these purposes. Differences in the estimates of the accuracy of the formulas are found. The proposed new formulas for calculating the number of intervals showed the best results. Calculations have been made to compare the work of the same formulas for the distribution of sample data according to the normal law and the Rayleigh law. http://www.tkea.com.ua/tkea/2017/3_2017/pdf/08.pdfentropy coefficientgrouping intervals numberinterval estimatesRayleigh distribution
collection DOAJ
language English
format Article
sources DOAJ
author Tynynyka A. N.
spellingShingle Tynynyka A. N.
Application of the entropic coefficient for interval number optimization during interval assessment
Tekhnologiya i Konstruirovanie v Elektronnoi Apparature
entropy coefficient
grouping intervals number
interval estimates
Rayleigh distribution
author_facet Tynynyka A. N.
author_sort Tynynyka A. N.
title Application of the entropic coefficient for interval number optimization during interval assessment
title_short Application of the entropic coefficient for interval number optimization during interval assessment
title_full Application of the entropic coefficient for interval number optimization during interval assessment
title_fullStr Application of the entropic coefficient for interval number optimization during interval assessment
title_full_unstemmed Application of the entropic coefficient for interval number optimization during interval assessment
title_sort application of the entropic coefficient for interval number optimization during interval assessment
publisher Politehperiodika
series Tekhnologiya i Konstruirovanie v Elektronnoi Apparature
issn 2225-5818
2309-9992
publishDate 2017-06-01
description In solving many statistical problems, the most precise choice of the distribution law of a random variable is required, the sample of which the authors observe. This choice requires the construction of an interval series. Therefore, the problem arises of assigning an optimal number of intervals, and this study proposes a number of formulas for solving it. Which of these formulas solves the problem more accurately? In [9], this question is investigated using the Pearson criterion. This article describes the procedure and on its basis gives formulas available in literature and proposed new formulas using the entropy coefficient. A comparison is made with the previously published results of applying Pearson's concord criterion for these purposes. Differences in the estimates of the accuracy of the formulas are found. The proposed new formulas for calculating the number of intervals showed the best results. Calculations have been made to compare the work of the same formulas for the distribution of sample data according to the normal law and the Rayleigh law.
topic entropy coefficient
grouping intervals number
interval estimates
Rayleigh distribution
url http://www.tkea.com.ua/tkea/2017/3_2017/pdf/08.pdf
work_keys_str_mv AT tynynykaan applicationoftheentropiccoefficientforintervalnumberoptimizationduringintervalassessment
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