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On quantiles estimation based on different stratified sampling with optimal allocation

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  • Hani Samawi
  • Arpita Chatterjee
  • Jingjing Yin
  • Haresh Rochani

Abstract

This work considers the problem of estimating a quantile function based on different stratified sampling mechanism. First, we develop an estimate for population quantiles based on stratified simple random sampling (SSRS) and extend the discussion for stratified ranked set sampling (SRSS). Furthermore, the asymptotic behavior of the proposed estimators are presented. In addition, we derive an analytical expression for the optimal allocation under both sampling schemes. Simulation studies are designed to examine the performance of the proposed estimators under varying distributional assumptions. The efficiency of the proposed estimates is further illustrated by analyzing a real data set from CHNS.

Suggested Citation

  • Hani Samawi & Arpita Chatterjee & Jingjing Yin & Haresh Rochani, 2019. "On quantiles estimation based on different stratified sampling with optimal allocation," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(6), pages 1529-1544, March.
    • Handle: RePEc:taf:lstaxx:v:48:y:2019:i:6:p:1529-1544
    DOI: 10.1080/03610926.2018.1433856
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