Missing Value Estimation and Analysis in Neutrosophic RBD
The Randomized Block Design (RBD) is a fundamental experimental design widely utilized in agricultural and industrial research to control variation by grouping experimental units into homogeneous blocks. Moreover, real-world experiments are often subjected to various sources of uncertainty, includin...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of New Mexico
2025-07-01
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| Series: | Neutrosophic Sets and Systems |
| Subjects: | |
| Online Access: | https://fs.unm.edu/NSS/12NeutrosophicRBD.pdf |
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| Summary: | The Randomized Block Design (RBD) is a fundamental experimental design widely utilized in agricultural and industrial research to control variation by grouping experimental units into homogeneous blocks. Moreover, real-world experiments are often subjected to various sources of uncertainty, including indeterminate, vague, imprecise, and erroneous data, which further complicate the analysis. To address these challenges, this paper introduces a novel neutrosophic analysis approach using Neutrosophic Logic for handling missing values in RBD under an uncertain environment. To further illustrate the practical application and effectiveness of the Neutrosophic Randomized Block Design (NRBD), an illustrative example from the medical field is presented. Further, simulation study is conducted to evaluate the performance of various parameters across different sample sizes. The analysis demonstrates the efficacy of Neutrosophic Randomized Block Design in preserving the statistical properties of the dataset and ensures more accurate and reliable experimental conclusions. |
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| ISSN: | 2331-6055 2331-608X |