This function provides a print method for the class "plsRmodel"
Usage
# S3 method for class 'plsRmodel'
print(x, ...)References
Nicolas Meyer, Myriam Maumy-Bertrand et Frédéric Bertrand (2010). Comparaison de la régression PLS et de la régression logistique PLS : application aux données d'allélotypage. Journal de la Société Française de Statistique, 151(2), pages 1-18. https://www.numdam.org/item/JSFS_2010__151_2_1_0/
Author
Frédéric Bertrand
frederic.bertrand@lecnam.net
https://fbertran.github.io/homepage/
Examples
data(Cornell)
XCornell<-Cornell[,1:7]
yCornell<-Cornell[,8]
modpls <- plsRglm(yCornell,XCornell,3,modele="pls")
#> ____************************************************____
#>
#> Model: pls
#>
#> ____Component____ 1 ____
#> ____Component____ 2 ____
#> ____Component____ 3 ____
#> ____Predicting X without NA neither in X nor in Y____
#> ****________________________________________________****
#>
class(modpls)
#> [1] "plsRglmmodel"
print(modpls)
#> Number of required components:
#> [1] 3
#> Number of successfully computed components:
#> [1] 3
#> Coefficients:
#> [,1]
#> Intercept 92.675989
#> X1 -9.828318
#> X2 -6.960181
#> X3 -16.666239
#> X4 -8.421802
#> X5 -4.388934
#> X6 10.161304
#> X7 -34.528959
#> Information criteria and Fit statistics:
#> AIC RSS_Y R2_Y R2_residY RSS_residY AIC.std
#> Nb_Comp_0 82.01205 467.796667 NA NA 11.0000000 37.010388
#> Nb_Comp_1 53.15173 35.742486 0.9235940 0.9235940 0.8404663 8.150064
#> Nb_Comp_2 41.08283 11.066606 0.9763431 0.9763431 0.2602256 -3.918831
#> Nb_Comp_3 32.06411 4.418081 0.9905556 0.9905556 0.1038889 -12.937550
#> DoF.dof sigmahat.dof AIC.dof BIC.dof GMDL.dof DoF.naive
#> Nb_Comp_0 1.000000 6.5212706 46.0708838 47.7893514 27.59461 1
#> Nb_Comp_1 2.740749 1.8665281 4.5699686 4.9558156 21.34020 2
#> Nb_Comp_2 5.085967 1.1825195 2.1075461 2.3949331 27.40202 3
#> Nb_Comp_3 5.121086 0.7488308 0.8467795 0.9628191 24.40842 4
#> sigmahat.naive AIC.naive BIC.naive GMDL.naive
#> Nb_Comp_0 6.5212706 46.0708838 47.7893514 27.59461
#> Nb_Comp_1 1.8905683 4.1699567 4.4588195 18.37545
#> Nb_Comp_2 1.1088836 1.5370286 1.6860917 17.71117
#> Nb_Comp_3 0.7431421 0.7363469 0.8256118 19.01033
rm(list=c("XCornell","yCornell","modpls"))