Almost unbiased modified ridge-type estimator: An application to tourism sector data in Egypt
2022
Omara, Tarek Mahmoud
This paper introduces an almost unbiased modified ridge-type estimator (AUMRTE) to avoid problems arising from multicollinearity. This estimator has the important features of the two important shrinkage estimators, the modified ridge-type estimator (MRTE) and almost unbiased estimator (AUE). We investigated the theoretical excellence of the proposed estimator according to the mean square error (MSE). We found that it has the superiority than the (MRTE) and almost unbiased two-parameter estimator (AUTE). Moreover, we run the simulation study, which depended on the simulated MSE (SMSE), squared bias (SB) and generalized cross-validation (GCV) as criteria to compare the estimators. The simulation results showed that the proposed estimator has the superiority than the estimators under comparison at several factors and at the same time, it works well at the high level of correlation. In addition, we investigated the behavior of the present estimator applying the real data. Under this trend, we applied the estimator to the tourism sector data in Egypt, which the results were consistent with the theoretical results.
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