Estimation of simple linear regression model using L ranked set sampling
In this article, L ranked-set sampling (LRSS) is used to estimate a simple linear regression model. We show that the estimated regression model based on LRSS is highly efficient compared to the estimators based on simple random sampling, Extreme ranked set sampling and ranked set sampling. Monte Carlo experiments are performed to assess the accuracy and the robustness of the LRSS estimates. The results are illustrated by an example.
|Journal||Int. J. Open Problems Compt. Math|