生物识别与生物统计学杂志

A Good Choice of Ridge Parameter with Minimum Mean Squared Error

Abstract

Iguernane M

In this paper, the problem of estimating the regression parameters is considered in a multiple regression model Y= X α + u hen the multicollinearity is present. Two suggested methods of finding the ridge regression parameter k are investigated and evaluated in terms of Mean Square Error (MSE) by simulation techniques. A number of factors that may affect the properties of these methods have been varied. Results of a simulation study indicate that with respect to MSE criteria, the suggested estimators perform better than both the ordinary least squares (OLS) estimator and the other estimators discussed here.