plsRglm (version 0.3.3)

tilt.bootplsglm: Tilted bootstrap for PLS models

Description

~~ A (1-5 lines) description of what the function does. ~~

Usage

tilt.bootplsglm(object, typeboot="plsmodel", statistic=coefs.plsRglm, R=c(499, 250, 250), alpha=c(0.025, 0.975), sim="ordinary", stype="i", index=1)

Arguments

object

~~Explain object here~~

typeboot

~~Explain typeboot here~~

statistic

~~Explain statistic here~~

R

~~Explain R here~~

alpha

~~Explain alpha here~~

sim

~~Explain sim here~~

stype

~~Explain stype here~~

index

~~Explain index here~~

Value

• ~Describe the value returned If it is a LIST, use
• comp1
  Description of 'comp1'
• comp2
  Description of 'comp2'
• ...

Details

~~ More details than the description above ~~

References

~put references to the literature/web site here ~

See Also

tilt.boot

Examples

data(aze_compl)
Xaze_compl<-aze_compl[,2:34]
yaze_compl<-aze_compl$y

dataset <- cbind(y=yaze_compl,Xaze_compl)

library(boot)
# Lazraq-Cl�roux PLS bootstrap Classic

# tilt.boot(data=dataset, statistic=coefs.plsRglm, R=c(499, 100, 100), alpha=c(0.025, 0.975), sim="ordinary", stype="i", index=1, nt=3, modele="pls-glm-logistic")
aze_compl.tilt.boot <- tilt.bootplsglm(plsRglm(yaze_compl,Xaze_compl,3, modele="pls-glm-logistic"), statistic=coefs.plsR, R=c(499, 100, 100), alpha=c(0.025, 0.975), sim="ordinary", stype="i", index=1)

boxplots.bootpls(aze_compl.tilt.boot,1:2)


# PLS bootstrap balanced

# tilt.boot(data=dataset, statistic=coefs.plsRglm, R=c(499, 250, 250), alpha=c(0.025, 0.975), sim="balanced", stype="i", index=1, nt=3, modele="pls-glm-logistic")
aze_compl.tilt.boot <- tilt.bootplsglm(plsRglm(yaze_compl,Xaze_compl,3, modele="pls-glm-logistic"), statistic=coefs.plsR, R=c(499, 100, 100), alpha=c(0.025, 0.975), sim="balanced", stype="i", index=1)


data(aze)
Xaze<-aze[,2:34]
yaze<-aze$y

dataset <- cbind(y=yaze,Xaze)

library(boot)
# tilt.boot(data=dataset, statistic=coefs.plsRglm, R=c(499, 100, 100), alpha=c(0.025, 0.975), sim="ordinary", stype="i", index=1, nt=3, modele="pls-glm-logistic")
aze.tilt.boot <- tilt.bootplsglm(plsRglm(yaze,Xaze,3, modele="pls-glm-logistic"), statistic=coefs.plsR, R=c(499, 100, 100), alpha=c(0.025, 0.975), sim="ordinary", stype="i", index=1)