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Research Article | Open Access

Algorithmic generation of imprecise data from uniform and Weibull distributions

Muhammad Aslam( )Osama H. Arif
Department of Statistics, Faculty of Science, King Abdulaziz University, Jeddah 21551, Saudi Arabia
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Abstract

This paper introduced the neutrosophic uniform distribution and innovative simulation methods to generate random numbers from the neutrosophic uniform distribution and the neutrosophic Weibull distribution. We introduced simulation methods and algorithms designed to handle indeterminacy for both of these distributions. We provided random numbers generated from both distributions across a range of parameter values and degrees of indeterminacy. Furthermore, we conducted a comparative analysis between the classical simulation method in classical statistics and the neutrosophic simulation method. Our findings reveal that the proposed neutrosophic simulation method generates random numbers of smaller magnitudes compared to the classical simulation method under classical statistics. This observation forms the basis of our conclusion.

CLC number: 62A86

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AIMS Mathematics
Pages 13087-13101

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Cite this article:
Aslam M, Arif OH. Algorithmic generation of imprecise data from uniform and Weibull distributions. AIMS Mathematics, 2024, 9(5): 13087-13101. https://doi.org/10.3934/math.2024639

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Received: 03 March 2024
Revised: 23 March 2024
Accepted: 29 March 2024
Published: 15 May 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)