AN EXAMINATION OF SOME SHRINKAGE ESTIMATORS FOR DIFFERENT SAMPLE SIZES AND CORRELATION STRUCTURES IN THE LINEAR REGRESSION

In the regression analysis, if there happens to be some kind of relation (multicollinearity) between independent variables, the Least Squares (LS) estimation method may lead to the use of wrong models and hence to wrong findings out of the model. Some methods have been developed to solve this problem; one of which is the "biased estimation method". In this study, a test statistics for Ridge and Liu estimators that are kinds of Shrinkage biased estimators is analyzed. Ridge and Liu estimators are examined via simulation study by the use of this test statistics, in terms of different correlation coefficients between the independent variables and different sample sizes.