Power ratio cum median-based ratio estimator of finite population mean with known population median

• Authors: Umar K. Abdullahi , Fidelis I. Ugwuowo , Nuanpan Lawson

Abstracts

EN

The search for an efficient estimator of the finite population mean has been a critical problem to the sample survey research community. This study is motivated by the fact that the conducted literature review showed that no research has developed such an average ratio estimator of the population mean that would utilize both the population and the sample medians of study variable, as well as the Srivastava (1967) estimator at a time. In this paper we proposed the power ratio cum median-based ratio estimator of the finite population mean, which is a function of two ratio estimators in the form of an average. The estimator assumes the population to be homogeneous and skewed. The properties (i.e. the Bias and the Mean Squared Error - MSE) of the proposed estimator were derived alongside its asymptotically optimum MSE. We demonstrated the efficiency of the proposed estimator jointly with its efficiency conditions by comparing it to selected estimators described in the literature. Empirically, a real-life dataset from the literature and a simulation study from two skewed distributions (Gamma and Weibull) were used to examine the efficiency gain. The empirical analysis and simulation study demonstrated that the efficiency gain is significant. Hence, the practical application of the proposed estimator is recommended, especially in socio-economic surveys.

Keywords

EN

finite population mean; bias; mean squared error; power estimator; medianbased; power ratio

• Publisher: Główny Urząd Statystyczny
• Journal: Statistics in Transition new series
• Year: 2023
• Volume: 24
• Issue: 5
• Pages: 35-44

Dates

published

2023

Contributors

author

Umar K. Abdullahi

• Department of Statistics, University of Nigeria

author

Fidelis I. Ugwuowo

• Department of Statistics, University of Nigeria

author

Nuanpan Lawson

• Department of Applied Statistics, Faculty of Applied Science, King Mongkut’s University of Technology North Bangkok, Wongsawang, Bangsue

References

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Identifiers

DOI

10.59170/stattrans-2023-062

Biblioteka Nauki

31342145