Proper linear model

In statistics, a proper linear model is a linear regression model in which the weights given to the predictor variables are chosen in such a way as to optimize the relationship between the prediction and the criterion. Simple regression analysis is the most common example of a proper linear model. Unit-weighted regression is the most common example of an improper linear model.

Bibliography

Dawes, R. M. (1979). "The robust beauty of improper linear models in decision making". American Psychologist. 34 (7): 571–582. doi:10.1037/0003-066X.34.7.571.

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