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

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Description

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

Usage

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kfolds2Chisqind(pls_kfolds)

Arguments

pls_kfolds

a kfold cross validated partial least squares regression glm model

Value

list

Individual PChisq vs number of components for the first group partition

...

...

list

Individual PChisq vs number of components for the last group partition

Note

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

Author(s)

Frédéric Bertrand
frederic.bertrand@math.unistra.fr
http://www-irma.u-strasbg.fr/~fbertran/

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://smf4.emath.fr/Publications/JSFdS/154_3/html/

See Also

kfolds2coeff, kfolds2Press, kfolds2Pressind, kfolds2Chisq, kfolds2Mclassedind and kfolds2Mclassed to extract and transforms results from kfold cross validation.

Examples

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## Not run: 
data("GasolineYield",package="betareg")
yGasolineYield <- GasolineYield$yield
XGasolineYield <- GasolineYield[,2:5]
bbb <- PLS_beta_kfoldcv(yGasolineYield,XGasolineYield,nt=3,modele="pls-beta")
kfolds2Chisqind(bbb)

## End(Not run)