| Autor: |
Abdulrahman AlAita, Muhammad Aslam, Khaled Al Sultan, Muhammad Saleem |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Journal of Big Data, Vol 11, Iss 1, Pp 1-13 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2196-1115 |
| DOI: |
10.1186/s40537-024-00970-1 |
| Popis: |
Abstract Objective This paper addresses the Graeco-Latin square design (GLSD) under neutrosophic statistics. In this work, we propose a novel approach for analyzing Graeco-Latin square designs using uncertain observations. Method This approach involves the determination of a neutrosophic ANOVA and the determination of the neutrosophic hypotheses and decision rule. Results The performance of the proposed design is evaluated using the numerical examples and simulation study. Conclusion Based on the results observed, it can be concluded that the GLSD under neutrosophic statistics performs better than the GLSD under classical statistics in the presence of uncertainty. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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