kfolds2CVinfos_beta: Extracts and computes information criteria and fits...

In plsRbeta: Partial Least Squares Regression for Beta Regression Models

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

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

Author(s)

Frédéric Bertrand
[e-mail]
https://fbertran.github.io/homepage/

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.

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)

plsRbeta documentation built on March 31, 2023, 11:01 p.m.