Solving multicollinearity problem of gross domestic product using ridge regression method
Multicollinearity
Ridge regression
General linear model
Gross Domestic Product
Mean square error
This study is dedicated to solving multicollinearity problem for the general linear model by using Ridge regression method. The basic formulation of this method and suggested forms for Ridge parameter is applied to the Gross Domestic Product data in Iraq. This data has normal distribution. The best linear regression model is obtained after solving multicollinearity problem with the suggesting of 10 k value.
