TY - JOUR
T1 - Regression Estimator Using Double Ranked Set Sampling
AU - Samawi, Hani
AU - Tawalbeh, Eman M.
N1 - Regression Estimator Using Double Ranked Set Sampling
PY - 2002
Y1 - 2002
N2 - 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.
AB - 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.
KW - Double extreme ranked set sample
KW - Regression estimator
UR - https://doi.org/10.24200/squjs.vol7iss2pp311-322
U2 - 10.24200/squjs.vol7iss2pp311-322
DO - 10.24200/squjs.vol7iss2pp311-322
M3 - Article
VL - 7
JO - Sultan Qaboos University Journal for Science
JF - Sultan Qaboos University Journal for Science
ER -