Optimal Neutrosophic Difference to Log-Type Estimator for  Population Mean: Some Numerical and Simulation Studies

SM Afsar Basha; Mahamood Usman

Authors

SM Afsar Basha Department of Mathematics (School of Advanced Sciences), Vellore Institute of Technology, Vellore 632014, India;
Mahamood Usman Department of Mathematics (School of Advanced Sciences), Vellore Institute of Technology, Vellore 632014, India;

Keywords:

Study variable; Auxiliary variable; Neutrosophic data; Mean squared error; Percent relative effi ciency

Abstract

Indeterminacy in the data are commonly observed in various fields like biomedicine, finance, mar
keting and other sphere of sciences, where classical statistical methods is a challenging task to deal such type
of data. This situation may be effecitively handled under neutrosophic framework. In this paper, we proposed
a novel optimal neutrosophic difference to log-type estimator for estimation of population mean, utilizing the
dual of an auxiliary variable. We derived the expression for bias and mean squared error (MSE) of the proposed
estimator up to the first-order of approximation and determined optimal situation for real constants based on
minimum MSE values. We conducted a numerical study using two real-life datasets related to temperature
and atmospheric conditions and the results are validated through a simulation study consisting two artificially
generated datasets. The findings indicates that the proposed neutrosophic estimator exhibited greater efficiency
compared to existing estimators when dealing with uncertain, indeterminate, interval and neutrosophic data.
These results highlights its potential applicability in analyzing uncertain or interval-valued data across various
scientific domains, including environmental monitoring, social sciences and atmospheric sciences.

DOI: 10.5281/zenodo.17081318