Amemiya's prediction error.
An object of class
Amemiya's Prediction Criterion penalizes R-squared more heavily than does adjusted R-squared for each addition degree of freedom used on the right-hand-side of the equation. The higher the better for this criterion.
((n + p) / (n - p))(1 - (R^2))
where n is the sample size, p is the number of predictors including the intercept and R^2 is the coefficient of determination.
Amemiya's prediction error of the model.
Amemiya, T. (1976). Selection of Regressors. Technical Report 225, Stanford University, Stanford, CA.
Judge, G. G., Griffiths, W. E., Hill, R. C., and Lee, T.-C. (1980). The Theory and Practice of Econometrics. New York: John Wiley & Sons.
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