regression estimator using double ranked set sampling

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ID: 227357
2002
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Abstract
The performance of a regression estimator based on the double ranked set sample (DRSS) scheme, introduced by Al-Saleh and Al-Kadiri (2000), is investigated when the mean of the auxiliary variable X is unknown. Our primary analysis and simulation indicates that using the DRSS regression estimator for estimating the population mean substantially increases relative efficiency compared to using regression estimator based on simple random sampling (SRS) or ranked set sampling (RSS) (Yu and Lam, 1997) regression estimator.  Moreover, the regression estimator using DRSS is also more efficient than the naïve estimators of the population mean using SRS, RSS (when the correlation coefficient is at least 0.4) and DRSS for high correlation coefficient (at least 0.91.) The theory is illustrated using a real data set of trees.
Reference Key
samawi2002sultanregression Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Hani M. Samawi;Eman M. Tawalbeh
Journal case reports in oncological medicine
Year 2002
DOI
10.24200/squjs.vol7iss2pp311-322
URL
https://journals.squ.edu.om/index.php/squjs/article/view/300
Keywords
Science (General)

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