Year: 2025
Type: article
Abstract: This paper proposes a neutrosophic exponential-type estimator for finite population mean estimation using auxiliary variables.Traditional statistical estimators often fall short when handling vague or uncertain data.Neutrosophic statistics provide a robust alternative, as they are specifically designed to address and incorporate indeterminacy.The mean square error (MSE) expressions are derived and the proposed estimator is compared with existing estimators through a numerical example using stock price data and a simulation study.Unlike traditional techniques, which provide point estimates, this method yields interval-based results and achieves a lower mean squared error (MSE), thereby enhancing the accuracy and dependability of the population mean estimation.
Authors: Anisha Taneja, Sachin Malik, Prem Shankar Jha
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7080719364
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