Computes PRESS for k-fold cross validated partial least squares regression models.

This function computes PRESS for k-fold cross validated partial least squares regression models.

Usage

kfolds2Press(pls_kfolds)

Arguments

pls_kfolds

a k-fold cross validated partial least squares regression model

Value

list

Press vs number of components for the first group partition

list()

...

list

Press vs number of components for the last group partition

Note

Use cv.plsR to create k-fold cross validated partial least squares regression models.

References

Nicolas Meyer, Myriam Maumy-Bertrand et Frédéric Bertrand (2010). Comparing the linear and the logistic PLS regression with qualitative predictors: application to allelotyping data. Journal de la Societe Francaise de Statistique, 151(2), pages 1-18. https://www.numdam.org/item/JSFS_2010__151_2_1_0/

See also

kfolds2coeff, kfolds2Pressind, kfolds2Mclassedind and kfolds2Mclassed to extract and transforms results from k-fold cross validation.

Author

Frédéric Bertrand
frederic.bertrand@lecnam.net
https://fbertran.github.io/homepage/

Examples

data(Cornell)
XCornell<-Cornell[,1:7]
yCornell<-Cornell[,8]
kfolds2Press(cv.plsR(object=yCornell,dataX=data.frame(scale(as.matrix(XCornell))[,]),
nt=6,K=12,NK=1,verbose=FALSE))
#> [[1]]
#> [1] 55.70774 41.43274 20.27397 21.24240 24.51801
#> 
kfolds2Press(cv.plsR(object=yCornell,dataX=data.frame(scale(as.matrix(XCornell))[,]),
nt=6,K=6,NK=1,verbose=FALSE))
#> [[1]]
#> [1] 51.17644 30.35008 19.73907 18.50431 29.77615
#> 
rm(list=c("XCornell","yCornell"))

# \donttest{
data(pine)
Xpine<-pine[,1:10]
ypine<-pine[,11]
kfolds2Press(cv.plsR(object=ypine,dataX=Xpine,nt=10,NK=1,verbose=FALSE))
#> [[1]]
#>  [1] 11.97615 12.00141 10.69039 10.30474 10.70328 10.57269 11.61333 11.70210
#>  [9] 11.98101 12.10232
#> 
kfolds2Press(cv.plsR(object=ypine,dataX=Xpine,nt=10,NK=2,verbose=FALSE))
#> [[1]]
#>  [1] 13.31403 13.81107 12.48677 13.62458 17.49581 18.48085 18.01662 17.96863
#>  [9] 17.94488 18.08595
#> 
#> [[2]]
#>  [1] 12.234426 12.271449 12.117853 10.314004  9.485939  9.493277  9.443128
#>  [8]  9.439081 10.075595 10.187946
#> 

XpineNAX21 <- Xpine
XpineNAX21[1,2] <- NA
kfolds2Press(cv.plsR(object=ypine,dataX=XpineNAX21,nt=10,NK=1,verbose=FALSE))
#> [[1]]
#> [1] 13.27636 13.56210 13.74395 12.95239 11.95871 12.45488 14.71568 18.22976
#> [9] 17.77810
#> 
kfolds2Press(cv.plsR(object=ypine,dataX=XpineNAX21,nt=10,NK=2,verbose=FALSE))
#> [[1]]
#> [1] 13.24267 16.33994 15.91731 14.25737 13.78751 14.49856 17.29316 17.10006
#> [9] 16.57428
#> 
#> [[2]]
#> [1] 12.22707 15.25976 17.52732 16.28843 14.28885 12.85276 13.40780 22.87170
#> [9] 42.66878
#> 
rm(list=c("Xpine","XpineNAX21","ypine"))
# }