| kfolds2Chisq {plsRbeta} | R Documentation |
Computes Predicted Chisquare for kfold cross validated partial least squares beta regression models.
Description
This function computes Predicted Chisquare for kfold cross validated partial least squares beta regression models.
Usage
kfolds2Chisq(pls_kfolds)
Arguments
pls_kfolds |
a kfold cross validated partial least squares regression glm model |
Value
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.
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,
kfolds2Press, kfolds2Pressind,
kfolds2Chisqind, kfolds2Mclassedind and
kfolds2Mclassed to extract and transforms results
from kfold cross validation.
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)