论文信息 - Parameters Estimation in a Simple Linear Regression Using Rank Set Sampling

Parameters Estimation in a Simple Linear Regression Using Rank Set Sampling

Ranked set sampling (RSS) as suggested by MCINTYRE (1952) and TAKAHASI and WAKIMOTO (1968) may be used to estimate the parameters of the simple regression line. The objective is to use the RSS method to increase the efficiency of the estimators relative to the simple random sampling (SRS) method. Estimators of the slope and intercept are considered. Computer simulated results are given, and an example using real data presented to illustrate the computations.

Hassen A. Muttlak | H. A. Muttlak

[1] J. Neter,et al. Applied Linear Regression Models , 1983 .

[2] Hassen A. Muttlak,et al. Ranked set sampling with respect to concomitant variables and with size biased probability of selection , 1990 .

[3] Hassen A. Muttlak,et al. Ranked set sampling with size-biased probability of selection , 1990 .

[4] S. Stokes,et al. Ranked set sampling with concomitant variables , 1977 .

[5] S. Stokes,et al. Estimation of Variance Using Judgment Ordered Ranked Set Samples , 1980 .

[6] L. K. Halls,et al. Trial of Ranked-Set Sampling for Forage Yields , 1966 .

[7] G. McIntyre,et al. A method for unbiased selective sampling, using ranked sets , 1952 .

[8] Kazumasa Wakimoto,et al. On unbiased estimates of the population mean based on the sample stratified by means of ordering , 1968 .

[9] J. L. Clutter,et al. Ranked Set Sampling Theory with Order Statistics Background , 1972 .