Learn R Programming

plsRbeta (version 0.2.6)

kfolds2Chisqind: Computes individual Predicted Chisquare for kfold cross validated partial least squares beta regression models.

Description

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

Usage

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()

list

Individual PChisq vs number of components for the last group partition

References

Fr<U+00E9>d<U+00E9>ric Bertrand, Nicolas Meyer, Mich<U+00E8>le Beau-Faller, Karim El Bayed, Izzie-Jacques Namer, Myriam Maumy-Bertrand (2013). R<U+00E9>gression B<U+00EA>ta PLS. Journal de la Soci<U+00E9>t<U+00E9> Fran<U+00E7>aise de Statistique, 154(3):143-159. http://publications-sfds.math.cnrs.fr/index.php/J-SFdS/article/view/215

See Also

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

Examples

Run this code
# NOT RUN {
# }
# 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)
# }
# NOT RUN {
# }

Run the code above in your browser using DataLab