Double Extreme-Cum-Median Ranked Set Sampling
Author Information
Author(s): Zubair Muhammad, Yasin Seyab, Al-Bossly Afrah, Ali Asad, Al Samman Fathia Moh., A. Almazah Mohammed M., Iqbal Kanwal
Primary Institution: Department of Economics and Statistics, Dr Hasan Murad School of Management, University of Management and Technology, Lahore, Pakistan
Hypothesis
The study proposes a new sampling method to improve mean estimation in heterogeneous populations with outliers.
Conclusion
The new sampling technique, DEMRSS, provides more efficient mean estimators compared to existing methods.
Supporting Evidence
- The proposed DEMRSS method outperforms traditional sampling methods in terms of efficiency.
- Simulation results indicate that DEMRSS yields higher percent relative efficiencies across various distributions.
- Real-life data analysis supports the findings from the simulation study.
Takeaway
This study introduces a new way to take samples that helps get better average results, especially when there are unusual values in the data.
Methodology
The study uses a combination of simulation and empirical data to evaluate the performance of the proposed sampling method.
Limitations
The study may not account for all types of distributions and ranking errors.
Participant Demographics
The study uses data from a population of children, focusing on weight and height.
Digital Object Identifier (DOI)
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