kfolds2Chisq function

Computes Predicted Chisquare for kfold cross validated partial least squares beta regression models.

This function computes Predicted Chisquare for kfold cross validated partial least squares beta regression models.

kfolds2Chisq(pls_kfolds)

Arguments

• pls_kfolds: a kfold cross validated partial least squares regression glm model

Returns

• list: Total Predicted Chisquare vs number of components for the first group partition - list(): ... - list: Total Predicted Chisquare vs number of components for the last group partition

Note

Use PLS_beta_kfoldcv to create kfold cross validated partial least squares regression glm and beta models.

Examples

## Not run:

data("GasolineYield",package="betareg")
yGasolineYield <- GasolineYield$yield
XGasolineYield <- GasolineYield[,2:5]
bbb <- PLS_beta_kfoldcv(yGasolineYield,XGasolineYield,nt=3,modele="pls-beta")
kfolds2Chisq(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, kfolds2Press, kfolds2Pressind, kfolds2Chisqind, 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/