Evaluating New Estimators in Ranked Set Sampling Using Auxiliary Variable
Abstract: This paper explores the application of Ranked Set Sampling (RSS) for estimating population means using auxiliary variables. We introduce two new estimators within the RSS framework and compare their performance to existing estimators in terms of mean square error and efficiency. Our findings indicate that the proposed estimators provide more efficient estimates under certain conditions, particularly when sample sizes are small and rankings are either perfect or imperfect. Empirical studies using simulations further validate the effectiveness of these new estimators, suggesting their potential for broader application in statistical analyses.
Keywords: Estimators, Population, Auxiliary Variable, Ranked Set Sampling, Efficiency
How to Cite?: Ruchi Gupta, Sangeeta Malik, "Evaluating New Estimators in Ranked Set Sampling Using Auxiliary Variable", Volume 13 Issue 8, August 2024, International Journal of Science and Research (IJSR), Pages: 1494-1497, https://www.ijsr.net/getabstract.php?paperid=SR24824152543, DOI: https://dx.doi.org/10.21275/SR24824152543