4R – Regression on Principal Components and Ridge Regression

Regression on Principal Components and Ridge Regression using BMDP Statistical Software Program 4R

4R produces a regression analysis for a dependent variable on a set of principal components computed from the independent variables. Use this program when the independent variables are highly correlated. 4R standardizes variables before computing principal components. A ridge regression option deflates correlations among the independent variables, thus, reducing the effects of multicollinearity. You can control the amount of ridging.

• Stepwise regression using principal components
• Eigenvectors, cumulative proportion of s² explained, R², regression coefficients, residual sum of squares, plots
• Option for printing principal component scores for each case
• View Program BMDP Program 4R Manual Chapter