Neutrosophic Log-Gamma Distribution and its Applications to Industrial Growth

This study suggests a novel statistical distribution known as the neutrosophic log gamma distribution (NLGD) for analyzing the interval value data. The proposed distribution is derived from the transformation method, utilizing the approach of neutrosophic logic. The statistical characteristics of the proposed are studied within a neutrosophic framework. Basic statistical properties such as moments of origin, mode, mean deviation, and other related functions that are commonly employed in statistical applications are derived. In addition to the basic properties of the model, the estimation approach of maximum likelihood is also studied. The derived estimators of the proposed model are further assessed by the simulation method. Comparative research using real-world examples shows that NLGD does a better job of modelling complicated industrial growth and production measures than standard distribution. Application of the proposed model improves our understanding of the theoretical component and our ability to forecast outcomes in statistical applications. This, in turn, leads to improved decision-making and operational efficiency in many industrial sectors

Publication Details

Journal
UNM’s Digital Repository (University of New Mexico)
Published
2024-09-01
Primary Topic
Fuzzy Systems and Optimization
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article

Neutrosophic Log-Gamma Distribution and its Applications to Industrial Growth

UNM’s Digital Repository (University of New Mexico)
Fuzzy Systems and Optimization
article

Neutrosophic Log-Gamma Distribution and its Applications to Industrial Growth

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Abstract

This study suggests a novel statistical distribution known as the neutrosophic log gamma distribution (NLGD) for analyzing the interval value data. The proposed distribution is derived from the transformation method, utilizing the approach of neutrosophic logic. The statistical characteristics of the proposed are studied within a neutrosophic framework. Basic statistical properties such as moments of origin, mode, mean deviation, and other related functions that are commonly employed in statistical applications are derived. In addition to the basic properties of the model, the estimation approach of maximum likelihood is also studied. The derived estimators of the proposed model are further assessed by the simulation method. Comparative research using real-world examples shows that NLGD does a better job of modelling complicated industrial growth and production measures than standard distribution. Application of the proposed model improves our understanding of the theoretical component and our ability to forecast outcomes in statistical applications. This, in turn, leads to improved decision-making and operational efficiency in many industrial sectors

UNM’s Digital Repository (University of New Mexico)
Openalex Percentile: Top 37%
Fuzzy Systems and Optimization
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Neutrosophic Log-Gamma Distribution and its Applications to Industrial Growth · UNM’s Digital Repository (University of New Mexico) (2024) | TGRS Research Map | TGRS