Work

Development of a novel estimator using auxiliary information under non-response: Application to radiation data sets

Year: 2025

Type: article

Abstract: Numerous disciplines rely on reliable population mean estimations under non-response conditions; this includes healthcare, economics, and weather forecasting, among others. Most research in sampling theory has focused on strategies to improve population mean estimate. In non-response scenarios, we still need a more precise estimate for population mean. In this study we develop an improved estimator employs an auxiliary variable within the framework of non-response using simple random sampling. Efficiency requirements are determined by comparing existing estimators with proposed estimator and looking at their mean squared errors and percentage relative efficiency. The empirical investigation makes use of radiation data sets and simulation investigation. The mean square errors and percentage relative efficiency of these estimators are examined through radiation data sets and simulation studies. The proposed estimators are significantly better than the existing ones, as shown by the numerical results. From the numerical results we see that our suggested estimator provide minimum mean square error and higher percentage relative efficiency. The significance and potential applications of our proposed estimator are highlighted by these outcomes.

Source: Journal of Radiation Research and Applied Sciences

DOI: 10.1016/j.jrras.2025.101401

Authors: Ahmed R. El-Saeed, Sohaib Ahmad, Badr Aloraini

Institutions: Imam Mohammad ibn Saud Islamic University, Abdul Wali Khan University Mardan, Shaqra University

Language: English

Topic: Survey Sampling and Estimation Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,400

Funders: Deanship of Scientific Research, Imam Mohammed Ibn Saud Islamic University, Al-Imam Muhammad Ibn Saud Islamic University