Functions calculating the Bayesian Informative Criterion , the Generalized Cross Validation criterion and the Corrected Akaike information criterion.

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`object` |
A fitted model object of class ibr. |

`...` |
Only for compatibility purpose with |

The ibr method for `BIC`

, `BIC.ibr()`

calculates
*log(sigma^2)+log(n)*df/n*, where *df* is the trace
of the smoother.

The ibr method for `GCV`

, `GCV.ibr()`

calculates
*log(sigma^2)-log(1-*df/n)*

The ibr method for `AICc`

, `AICc.ibr()`

calculates
*log(sigma^2)+1+(2*(df+1))/(n-df-2)*.

Returns a numeric value with the corresponding BIC, GCV or AICc.

Pierre-Andre Cornillon, Nicolas Hengartner and Eric Matzner-Lober.

Hurvich, C. M., Simonoff J. S. and Tsai, C. L. (1998) Smoothing
Parameter Selection in Nonparametric Regression Using an Improved Akaike
Information Criterion. *Journal of the Royal Statistical Society, Series B*, 60, 271-293 .

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