On Neutrosophic Mean Estimation for Populations with Imprecise Measurements

Accepted March 2026

Abstract

In the fields of engineering, biological, physical, behavioral, and social sciences, data points with incomplete, imprecise, or vague measurements are inevitable issues. In populations with imprecise measurements, the traditional estimation methods may yield misleading results. We present an optimal neutrosophic estimator for populations containing imprecise, incomplete, undefined and vague values. The neutrosophic properties and efficiency conditions have been studied. To demonstrate efficiency, some real-life populations with imprecise values have been used. We find that the proposed neutrosophic estimator performs the best among all of its competitors. These results make the proposed neutrosophic estimator the most appropriate for real-world imprecise data.