Combining Two Auxiliary Variables for Elevated Estimation of Finite Population Mean under Neutrosophic Framework

Abstract

 Typically, most researchers rely on precise data for estimating population parameters using 
classical statistical methods. However, there are scenarios where dealing with uncertain and imprecise 
data in the form of intervals becomes necessary. To tackle this challenge, various adaptations of classical 
estimators, such as the neutrosophic ratio estimator and their improved ones, have emerged. This article 
introduces a novel estimator known as the neutrosophic ratio-cum-product exponential estimator 
combining two auxiliary variables, specifically designed for the elevated estimation of population mean 
in such situations. Performance evaluation is conducted using metrics like Mean Square Error (MSE) and 
Percentage Relative Efficiency (PRE). The effectiveness of the proposed estimator is demonstrated 
through both empirical and simulation studies. Additionally, its practical applicability is showcased using 
agricultural data. The results illustrate that the proposed estimator surpasses all other estimators 
discussed in this paper. To justify the usefulness of neutrosophic estimators over their classical ones, a 
simulation study is also made. Simulation results obtained for classical estimators have also been 
compared with their neutrosophic adaptations.

DOI: 10.5281/zenodo.13997073