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Full-Text Articles in Physical Sciences and Mathematics
The Performance Of Some Restricted Estimators In Restricted Linear Regression Model, Bader Aboud Mohammed, Mustafa Ismaeel Naif
The Performance Of Some Restricted Estimators In Restricted Linear Regression Model, Bader Aboud Mohammed, Mustafa Ismaeel Naif
Al-Qadisiyah Journal of Pure Science
In the linear regression model, the restricted biased estimation as one of important methods to addressing the high variance and the multicollinearity problems. In this paper, we make the simulation study of the some restricted biased estimators. The mean square error (MME) criteria are used to make a comparison among them. According to the simulation study we observe that, the performance of the restricted modified unbiased ridge regression estimator (RMUR) was proposed by Bader and Alheety (2020) is better than of these estimators. Numerical example have been considered to illustrate the performance of the estimators.
The Performance Of Some Biased Estimators With Different Biased Parameter In Linear Regression Model, Mustafa Nadhim Lattef, Mustafa I. Alheety
The Performance Of Some Biased Estimators With Different Biased Parameter In Linear Regression Model, Mustafa Nadhim Lattef, Mustafa I. Alheety
Al-Qadisiyah Journal of Pure Science
To circumvent the problem of multicollinearity, biased estimation method has been suggested to improve the precision of estimators. In this paper, we study types of biased estimators that can help to reduce the effect of multicollinearity on estimation. A simulation study is carried out to study the relative effectiveness of certain types of biased estimators in comparison to some proposed estimated ridge parameter (k) that have been shown in the literature . Moreover, a real data set has been considered to support the simulation results based on the estimated mean square error criterion.