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

Description

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.

Usage

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kfolds2CVinfos_beta(pls_kfolds, MClassed = FALSE)

Arguments

pls_kfolds

an object computed using PLS_beta_kfoldcv

MClassed

should number of miss classed be computed

Details

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

Value

list

table of fit statistics for first group partition

...

...

list

table of fit statistics for last group partition

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

Examples

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## 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)

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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