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

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.