kfolds2CVinfos_beta function

Extracts and computes information criteria and fits statistics for kfold cross validated partial least squares beta regression models

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.

kfolds2CVinfos_beta(pls_kfolds, MClassed = FALSE)

Arguments

• pls_kfolds: an object computed using PLS_beta_kfoldcv
• MClassed: should number of miss classed be computed

Returns

• list: table of fit statistics for first group partition

• list(): ... - list: table of fit statistics for last group partition

Details

The Mclassed option should only set to TRUE if the response is binary.

Examples

## 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)

References

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://publications-sfds.math.cnrs.fr/index.php/J-SFdS/article/view/215

See Also

kfolds2coeff, kfolds2Pressind, kfolds2Press, kfolds2Mclassedind and kfolds2Mclassed to extract and transforms results from kfold cross validation.

Author(s)

Frédéric Bertrand

frederic.bertrand@utt.fr

https://fbertran.github.io/homepage/