Performance of Some New Ridge Regression Estimators

Abstract

In the ridge regression analysis, the estimation of ridge parameter k is an important problem. Many methods are available for estimating such a parameter. This article has considered some of these methods and also proposed some new estimators based on generalized ridge regression approach. A simulation study has been made to evaluate the performance of proposed estimators based on the minimum mean squared error (MSE) criterion. The simulation study indicates that under certain conditions the proposed estimators perform well compared to least squares estimators (LSE) and other popular existing estimators. Finally, a numerical example has been analyzed and its findings support the simulation results to some extent.

Keywords:

• MSE
• Ridge regression
• Signal-to-noise
• Simulation study

Acknowledgment

The author is thankful to the College of Arts and Sciences of Florida International University for providing him some research facilities.