Summary method for plsR models

This function provides a summary method for the class "cv.plsRmodel"

Usage

# S3 method for class 'cv.plsRmodel'
summary(object, ...)

Arguments

object

an object of the class "cv.plsRmodel"

...

further arguments to be passed to or from methods.

Value

An object of class "summary.cv.plsRglmmodel".

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

summary

Author

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

Examples

data(Cornell)
summary(cv.plsR(Y~.,data=Cornell,nt=10,K=6, verbose=FALSE), verbose=FALSE)
#> [[1]]
#>                AIC     Q2cum_Y LimQ2_Y       Q2_Y  PRESS_Y      RSS_Y      R2_Y
#> Nb_Comp_0 82.01205          NA      NA         NA       NA 467.796667        NA
#> Nb_Comp_1 53.15173   0.8496596  0.0975  0.8496596 70.32872  35.742486 0.9235940
#> Nb_Comp_2 41.08283   0.7926079  0.0975 -0.3794841 49.30619  11.066606 0.9763431
#> Nb_Comp_3 32.06411   0.5788646  0.0975 -1.0306237 22.47211   4.418081 0.9905556
#> Nb_Comp_4 33.76477  -1.6107564  0.0975 -5.1993283 27.38914   4.309235 0.9907882
#> Nb_Comp_5 33.34373 -17.5479050  0.0975 -6.1044181 30.61461   3.521924 0.9924713
#> Nb_Comp_6 35.25533          NA  0.0975         NA       NA   3.496074 0.9925265
#>              AIC.std  DoF.dof sigmahat.dof    AIC.dof    BIC.dof GMDL.dof
#> Nb_Comp_0  37.010388 1.000000    6.5212706 46.0708838 47.7893514 27.59461
#> Nb_Comp_1   8.150064 2.740749    1.8665281  4.5699686  4.9558156 21.34020
#> Nb_Comp_2  -3.918831 5.085967    1.1825195  2.1075461  2.3949331 27.40202
#> Nb_Comp_3 -12.937550 5.121086    0.7488308  0.8467795  0.9628191 24.40842
#> Nb_Comp_4 -11.236891 5.103312    0.7387162  0.8232505  0.9357846 24.23105
#> Nb_Comp_5 -11.657929 6.006316    0.7096382  0.7976101  0.9198348 28.21184
#> Nb_Comp_6  -9.746328 7.000002    0.7633343  0.9711322  1.1359502 33.18348
#>           DoF.naive sigmahat.naive  AIC.naive  BIC.naive GMDL.naive
#> Nb_Comp_0         1      6.5212706 46.0708838 47.7893514   27.59461
#> Nb_Comp_1         2      1.8905683  4.1699567  4.4588195   18.37545
#> Nb_Comp_2         3      1.1088836  1.5370286  1.6860917   17.71117
#> Nb_Comp_3         4      0.7431421  0.7363469  0.8256118   19.01033
#> Nb_Comp_4         5      0.7846050  0.8721072  0.9964867   24.16510
#> Nb_Comp_5         6      0.7661509  0.8804809  1.0227979   28.64206
#> Nb_Comp_6         7      0.8361907  1.1070902  1.3048716   33.63927
#> attr(,"computed_nt")
#> [1] 6
#> 
#> attr(,"class")
#> [1] "summary.cv.plsRmodel"