| kfolds2CVinfos_beta {plsRbeta} | R Documentation |
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 |
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
frederic.bertrand@utt.fr
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)