Authors' ORCIDs
Anchal Yadav: https://orcid.org/0009-0006-1664-0100
Anuj Yadav: https://orcid.org/0009-0005-5650-2549
Article Type
Research Article
Abstract
This study develops a generalized neutrosophic ratio-type estimator for estimating the population mean by incorporating information from two auxiliary variables under Simple Random Sampling Without Replacement (SRSWOR). The proposed methodology extends the conventional single-auxiliary-variable approach by jointly incorporating bivariate auxiliary information within the neutrosophic framework, thereby accounting for uncertainty, indeterminacy, and inconsistency in the available information. The bias and mean squared error of the proposed estimator are derived using first-order approximations, and the corresponding efficiency conditions are established through theoretical comparisons with existing neutrosophic estimators. The performance of the proposed estimator is further examined using a real medical dataset represented in the neutrosophic framework. In addition, a simulation study is conducted under different population configurations to assess its performance under varying levels of uncertainty and association between the study and auxiliary variables. The theoretical, empirical, and simulation analyses provide a comprehensive evaluation of the proposed bivariate neutrosophic estimation methodology.
Keywords
Dual auxiliary variable, Exponential estimator, Mean squared error (MSE), Percentage relative efficiency (PRE), Simulation study
How to Cite
Yadav, Anchal and Yadav, Anuj
(2026)
"A Unified Framework for Neutrosophic Estimation Using Fractional Power, Exponential, and Logarithmic Functions with Bivariate Auxiliary Information,"
Neutrosophic Systems with Applications: Vol. 26:
Iss.
8, Article 2.
DOI: https://doi.org/10.63689/2993-7159.1358
