Proper linear model
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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.
[edit] Bibliography
Dawes, R. M. (1979). The robust beauty of improper linear models in decision making. American Psychologist, 34, 571–582.
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