Description Usage Arguments Details Value References See Also Examples

Estimated mean square error of prediction.

1 | ```
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`

1 2 |

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