This function computes information criteria for existing plsR model using Degrees of Freedom estimation.

1 | ```
infcrit.dof(modplsR, naive = FALSE)
``` |

`modplsR` |
A plsR model i.e. an object returned by one of the functions |

`naive` |
A boolean. |

If `naive=FALSE`

returns AIC, BIC and gmdl values for estimated and naive degrees of freedom. If `naive=TRUE`

returns `NULL`

.

`matrix` |
AIC, BIC and gmdl values or |

Frederic Bertrand

frederic.bertrand@math.unistra.fr

http://www-irma.u-strasbg.fr/~fbertran/

M. Hansen, B. Yu. (2001). Model Selection and Minimum Descripion Length Principle, *Journal of the American Statistical Association*, 96, 746-774.

N. Kraemer, M. Sugiyama. (2011). The Degrees of Freedom of Partial Least Squares Regression. *Journal of the American Statistical Association*, 106(494), 697-705.

N. Kraemer, M. Sugiyama, M.L. Braun. (2009). Lanczos Approximations for the Speedup of Kernel Partial Least Squares Regression, *Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS)*, 272-279.

`plsR.dof`

for degrees of freedom computation and `infcrit.dof`

for computing information criteria directly from a previously fitted plsR model.

1 2 3 4 5 |

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