Missing Value Estimation and Analysis in Neutrosophic RBD

Masum Raj; S. C. Malik; Rahul Thakur

Authors

Masum Raj Department of Mathematics, Institute of Applied Sciences and Humanities, G.L.A. University, Mathura, U.P., India;
S. C. Malik Department of Statistics, Maharshi Dayanand University, Rohtak, Haryana, India (124001);
Rahul Thakur Department of Statistics, Maharshi Dayanand University, Rohtak, Haryana, India (124001);

Keywords:

Randomized Block Design, Neutrosophic Logic, Missing Value, Analysis of Variance, Neutrosophic Randomized Block Design.

Abstract

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.

DOI: 10.5281/zenodo.15625298