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Research Article | Open Access

Some Tsallis entropy measures in concomitants of generalized order statistics under iterated FGM bivariate distribution

I. A. Husseiny1( )M. Nagy2A. H. Mansi3M. A. Alawady1
Department of Mathematics, Faculty of Science, Zagazig University, Zagazig 44519, Egypt
Department of Statistics and Operations Research, College of Science, King Saud University, P.O.Box 2455, Riyadh 11451, Saudi Arabia
DICA, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133, Milano, MI, Italy
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Abstract

Shannon differential entropy is extensively applied in the literature as a measure of dispersion or uncertainty. Nonetheless, there are other measurements, such as the cumulative residual Tsallis entropy (CRTE), that reveal interesting effects in several fields. Motivated by this, we study and compute Tsallis measures for the concomitants of the generalized order statistics (CGOS) from the iterated Farlie-Gumbel-Morgenstern (IFGM) bivariate family. Some newly introduced information measures are also being considered for CGOS within the framework of the IFGM family, including Tsallis entropy, CRTE, and an alternative measure of CRTE of order η. Applications of these results are given for order statistics and record values with uniform, exponential, and power marginals distributions. In addition, the empirical cumulative Tsallis entropy is suggested as a method to calculate the new information measure. Finally, a real-world data set has been analyzed for illustrative purposes, and the performance is quite satisfactory.

CLC number: 62G30, 94A17

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AIMS Mathematics
Pages 23268-23290

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Cite this article:
Husseiny IA, Nagy M, Mansi AH, et al. Some Tsallis entropy measures in concomitants of generalized order statistics under iterated FGM bivariate distribution. AIMS Mathematics, 2024, 9(9): 23268-23290. https://doi.org/10.3934/math.20241131

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Received: 06 June 2024
Revised: 01 July 2024
Accepted: 23 July 2024
Published: 15 September 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)