The Nature of Collinearity

Abstract

Collinearity is viewed as an expression of the shape of the domain defined by the regressor variables. By applying the singular value decomposition to the matrix of regressors, a geometrical figure is derived, called the “effective prediction domain” (EPD), within which prediction from the regression value is valid. The further away the prediction point is from the EPD, the less confidence one can have in the predicted value.

• Collinearity
• Multiple Regression
• Prediction Domain
• Singular Value Decomposition

Additional information

Notes on contributors

John Mandel

Dr. Mandel is a Senior Statistical Consultant at the National Measurement Laboratory. He is a Fellow of ASQC.