ols_fpe {olsrr} | R Documentation |
Estimated mean square error of prediction.
ols_fpe(model)
model |
An object of class |
Computes the estimated mean square error of prediction for each model selected assuming that the values of the regressors are fixed and that the model is correct.
MSE((n + p) / n)
where MSE = SSE / (n - p)
, n is the sample size and p is the number of predictors including the intercept
Final prediction error of the model.
Akaike, H. (1969). “Fitting Autoregressive Models for Prediction.” Annals of the Institute of Statistical Mathematics 21:243–247.
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.
Other model selection criteria: ols_aic
,
ols_apc
, ols_hsp
,
ols_mallows_cp
, ols_msep
,
ols_sbc
, ols_sbic
model <- lm(mpg ~ disp + hp + wt + qsec, data = mtcars)
ols_fpe(model)