This function extracts and computes information criteria and fits statistics for kfold cross validated partial least squares beta regression models for both formula or classic specifications of the model.

1 | ```
kfolds2CVinfos_beta(pls_kfolds, MClassed = FALSE)
``` |

`pls_kfolds` |
an object computed using |

`MClassed` |
should number of miss classed be computed |

The Mclassed option should only set to `TRUE`

if the response is binary.

`list` |
table of fit statistics for first group partition |

`...` |
... |

`list` |
table of fit statistics for last group partition |

Frédéric Bertrand

frederic.bertrand@math.unistra.fr

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

Frédéric Bertrand, Nicolas Meyer, Michèle Beau-Faller, Karim El Bayed, Izzie-Jacques Namer, Myriam Maumy-Bertrand (2013). Régression Bêta PLS. *Journal de la Société Française de Statistique*, **154**(3):143-159.
http://smf4.emath.fr/Publications/JSFdS/154_3/html/

`kfolds2coeff`

, `kfolds2Pressind`

, `kfolds2Press`

, `kfolds2Mclassedind`

and `kfolds2Mclassed`

to extract and transforms results from kfold cross validation.

1 2 3 4 5 6 | ```
## Not run:
data("GasolineYield",package="betareg")
bbb <- PLS_beta_kfoldcv_formula(yield~.,data=GasolineYield,nt=3,modele="pls-beta")
kfolds2CVinfos_beta(bbb)
## End(Not run)
``` |

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