using maximum likelihood (ML). The ML method is very sensitive to multicollinearity. Therefore, we present a new Poisson … calculate the mean squared error (MSE) using Monte Carlo simulations. The result from the simulation study shows that the PRR …

the random error and increasing the correlation between the independent variables have negative effect on the MSE. When … the sample size increases the MSE decreases even when the correlation between the independent variables and the variance … of the random error are large. In all situations, the proposed estimators have smaller MSE than the ordinary least …

performance of these new estimators are judged by calculating the mean square error (MSE) using Monte Carlo simulations. In the …

classical maximum likelihood (ML) method in the presence of multicollinearity since the mean squared error (MSE) of ML becomes … MSE and mean absolute error (MAE) are calculated it is shown that when the Liu estimator is applied with these proposed …

developed by Alkhamisi and Shukur (2008), AS, when the explanatory variables are affected by multicollinearity. Nine ridge …

Mean Squared Error (MSE) of parameter estimators, is evaluated. …

induces multicollinearity problems since all non-zero values are equal between the interaction term and the regressor. In this … AIR using the mean square error (MSE) performance criterion. The result from the simulation study confirms our hypothesis … that AIR always should be preferred to OLS since it has a lower estimated MSE. Moreover, the advantages of our new method …

) test to a new ridge regression GC test (RRGC), in the presence of multicollinearity. The investigation has been carried out …-rejects the true null hypothesis when there are relatively high (but empirically common levels of) multicollinearity, while it is …