A Retrospective Study on Neutrosophic Distributions and Their  Applications

Jismi Mathew; Milin K. Anil

Authors

Jismi Mathew Department of Statistics, Vimala College (Autonomous), Thrissur, Kerala, India;
Milin K. Anil Department of Statistics, Vimala College (Autonomous), Thrissur, Kerala, India;

Keywords:

Neutrosophic Distributions, Uncertainty Modeling, Comparison with Classical Distributions

Abstract

In recent years, Neutrosophic statistics has emerged as a powerful framework for
handling uncertainty, indeterminacy, and imprecision in data. This review paper presents a
comprehensive retrospective analysis of Neutrosophic distributions, tracing their theoretical
foundations, historical evolution, and methodological advancements. The study systematically
compares Neutrosophic distributions with classical probability distributions, emphasizing their
unique ability to explicitly model indeterminacy through the incorporation of truth, indeter
minacy, and falsity components. Key Neutrosophic distributions introduced in the literature
are discussed alongside their related terms, with a tabular presentation to aid clarity. The
methodologies employed in existing studies are examined in detail. Particular attention is
given to their applications in biomedical research, where uncertainty is a critical factor in
decision-making and data interpretation. The advantages, limitations, and challenges associated
with Neutrosophic models are also analyzed. Finally, future research directions are proposed,
including the development of new distributions, improved computational tools, and broader
interdisciplinary applications. This review underscores the growing significance of Neutrosophic
distributions as a generalization of classical models, offering a more realistic approach to data
analysis in complex, uncertain environments.