Neutrosophic Exponential Ratio-Type Estimator for Finite Population Mean in Stratified Sampling

Abstract

This paper introduces an innovative neutrosophic exponential ratio-type estimator for 
estimating finite population means in stratified sampling environments with indeterminate data. 
Building upon classical exponential estimators and neutrosophic statistics, we develop a robust 
estimator that effectively handles uncertainty through interval-valued representations. The 
proposed estimator combines the strengths of exponential ratio estimation with neutrosophic 
weighting to achieve enhanced precision in stratified sampling scenarios. We derive the bias and 
mean square error (MSE) expressions under first-order approximation and demonstrate through 
empirical analysis using climate data that our estimator outperforms existing neutrosophic stratified 
estimators in terms of efficiency and reliability.

DOI: 10.5281/zenodo.17096019