Work

Developing and evaluating efficient estimators for finite population mean in two-phase sampling

Year: 2025

Type: article

Abstract: The estimator development process is more efficient when additional information is used. However, occasionally, it is necessary to use information regarding unknown population parameters. In these cases, we chose two-phase sampling by substituting the population mean of the supplemental variable with the sample mean from first-phase sampling. The goal of this project was to develop effective estimators of the finite population mean in a two-phase sampling scenario with a single auxiliary variable. Under certain conditions, the recommended estimators outperform the current estimators, producing biased and Mean Square Error (MSE) expressions. Empirical and theoretical comparisons of the proposed families were conducted using real and simulated data. We found that the proposed families were more effective in the two-phase sampling situation than in all-population mean estimators.

Source: AIMS Mathematics

DOI: 10.3934/math.2025408

Authors: Khazan Sher, Muhammad Ameeq, Sidra Naz, Basem A. Alkhaleel, Muhammad Muneeb Hassan, Olayan Albalawi

Institutions: University of Peshawar, Islamia University of Bahawalpur, King Saud University, University of Tabuk

Language: English

Topic: Survey Sampling and Estimation Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,200

Funder: King Saud University