Modified Robust Ridge M-Estimators in Two-Parameter Ridge Regression Model
Seyab Yasin, Sultan Salem, Hamdi Ayed, Shahid Kamal, Muhammad Suhail, Yousaf Ali Khan
Abstract
The methods of two-parameter ridge and ordinary ridge regression are very sensitive to the presence of the joint problem of multicollinearity and outliers in the y-direction. To overcome this problem, modified robust ridge M-estimators are proposed. The new estimators are then compared with the existing ones by means of extensive Monte Carlo simulations. According to mean squared error (MSE) criterion, the new estimators outperform the least square estimator, ridge regression estimator, and two-parameter ridge estimator in many considered scenarios. Two numerical examples are also presented to illustrate the simulation results.
Topics & Concepts
MulticollinearityEstimatorRidgeMean squared errorMathematicsOutlierMonte Carlo methodRobust regressionStatisticsRegressionRegression analysisApplied mathematicsGeologyPaleontologyAdvanced Statistical Methods and ModelsAdvanced Statistical Process MonitoringStatistical Methods and Inference