An Efficient Modified Ratio Estimator under Stratified Ranked Set Sampling

Authors

  • Zahid Khan Department of Statistics, University of Malakand, Chakdara, Dir Lower, Pakistan
  • Amina Shahzadi Department of Statistics, GC University Lahore, Pakistan
  • Ammara Nawaz Cheema Department of Mathematics, Air University Islamabad, Pakistan
  • Bashir ul Haq M. Phil Scholar, Department of Statistics, University of Malakand, Pakistan
  • Maria Malik COMSATS University Islamabad, Pakistan

DOI:

https://doi.org/10.63278/1497

Keywords:

efficiency, population mean, ratio estimators, stratified ranked set sampling, conditions.

Abstract

Stratified Ranked Set Sampling (SRSS) merges the benefits of stratification and Ranked Set Sampling (RSS) to yield an unbiased estimate of the population mean, with potential improvements in efficiency. This paper introduces modified ratio estimators for determining the mean of a finite population, using the first and third quartiles as supplementary information within the SRSS design. Results indicate that these estimators perform better compared to those based on Stratified Simple Random Sampling (StSRS). Expressions for bias and mean squared error (MSE) are derived for the proposed estimators. Theoretical analysis suggests that, under certain conditions, these estimators are more efficient than those used in StSRS and some existing SRSS methods.

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How to Cite

Zahid Khan, Amina Shahzadi, Ammara Nawaz Cheema, Bashir ul Haq, and Maria Malik. 2024. “An Efficient Modified Ratio Estimator under Stratified Ranked Set Sampling”. Metallurgical and Materials Engineering 30 (4):677-86. https://doi.org/10.63278/1497.

Issue

Vol. 30 No. 4 (2024)

Section

Research

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Copyright (c) 2024 Zahid Khan, Amina Shahzadi, Ammara Nawaz Cheema, Bashir ul Haq, Maria Malik

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