bootplsbeta: Non-parametric Bootstrap for PLS beta regression models

In plsRbeta: Partial Least Squares Regression for Beta Regression Models

Non-parametric Bootstrap for PLS beta regression models

Description

Provides a wrapper for the bootstrap function boot from the boot R package.
Implements non-parametric bootstrap for PLS beta regression models by case resampling.

Usage

bootplsbeta(
  object,
  typeboot = "plsmodel",
  R = 250,
  statistic = NULL,
  sim = "ordinary",
  stype = "i",
  stabvalue = 1e+06,
  ...
)

Arguments

object	An object of class plsRbetamodel to bootstrap
typeboot	The type of bootstrap. Either (Y,X) boostrap (typeboot="plsmodel") or (Y,T) bootstrap (typeboot="fmodel_np"). Defaults to (Y,T) resampling.
R	The number of bootstrap replicates. Usually this will be a single positive integer. For importance resampling, some resamples may use one set of weights and others use a different set of weights. In this case R would be a vector of integers where each component gives the number of resamples from each of the rows of weights.
statistic	A function which when applied to data returns a vector containing the statistic(s) of interest. statistic must take at least two arguments. The first argument passed will always be the original data. The second will be a vector of indices, frequencies or weights which define the bootstrap sample. Further, if predictions are required, then a third argument is required which would be a vector of the random indices used to generate the bootstrap predictions. Any further arguments can be passed to statistic through the ... argument.
sim	A character string indicating the type of simulation required. Possible values are "ordinary" (the default), "balanced", "permutation", or "antithetic".
stype	A character string indicating what the second argument of statistic represents. Possible values of stype are "i" (indices - the default), "f" (frequencies), or "w" (weights).
stabvalue	A value to hard threshold bootstrap estimates computed from atypical resamplings.
...	Other named arguments for statistic which are passed unchanged each time it is called. Any such arguments to statistic should follow the arguments which statistic is required to have for the simulation. Beware of partial matching to arguments of boot listed above.

Details

More details on bootstrap techniques are available in the help of the boot function.

Value

An object of class "boot". See the Value part of the help of the function boot.

Author(s)

Frédéric Bertrand
[e-mail]
https://fbertran.github.io/homepage/

References

Frédéric Bertrand, Nicolas Meyer, Michèle Beau-Faller, Karim El Bayed, Izzie-Jacques Namer, Myriam Maumy-Bertrand (2013). Régression Bêta PLS. Journal de la Société Française de Statistique, 154(3):143-159. http://publications-sfds.math.cnrs.fr/index.php/J-SFdS/article/view/215

See Also

boot

Examples

data("GasolineYield",package="betareg")

# Std coefficients
modplsbeta <- plsRbeta(yield~., data=GasolineYield, nt=3, modele="pls-beta")
GazYield.boot <- bootplsbeta(modplsbeta, sim="ordinary", stype="i", R=250)
boot::boot.ci(GazYield.boot, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=1)
boot::boot.ci(GazYield.boot, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=2)
boot::boot.ci(GazYield.boot, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=3)
boot::boot.ci(GazYield.boot, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=4)
boot::boot.ci(GazYield.boot, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=5)
boot::boot.ci(GazYield.boot, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=6)

plsRglm::boxplots.bootpls(GazYield.boot)
plsRglm::confints.bootpls(GazYield.boot)
plsRglm::plots.confints.bootpls(plsRglm::confints.bootpls(GazYield.boot))

#Raw coefficients
modplsbeta <- plsRbeta(yield~.,data=GasolineYield,nt=3, modele="pls-beta")
GazYield.boot.raw <- bootplsbeta(modplsbeta, sim="ordinary", stype="i", 
R=250, statistic=coefs.plsRbeta.raw)
boot::boot.ci(GazYield.boot.raw, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=1)
boot::boot.ci(GazYield.boot.raw, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=2)
boot::boot.ci(GazYield.boot.raw, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=3)
boot::boot.ci(GazYield.boot.raw, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=4)
boot::boot.ci(GazYield.boot.raw, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=5)
boot::boot.ci(GazYield.boot.raw, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=6)

plsRglm::boxplots.bootpls(GazYield.boot.raw)
plsRglm::confints.bootpls(GazYield.boot.raw)
plsRglm::plots.confints.bootpls(plsRglm::confints.bootpls(GazYield.boot.raw))


plot(GazYield.boot.raw,index=2)
boot::jack.after.boot(GazYield.boot.raw, index=2, useJ=TRUE, nt=3)
plot(GazYield.boot.raw, index=2,jack=TRUE)

# PLS bootstrap balanced

GazYield.boot.bal <- bootplsbeta(plsRbeta(yield~.,data=GasolineYield,nt=3,
modele="pls-beta"), sim="balanced", stype="i", R=250)
boot::boot.ci(GazYield.boot.bal, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=1)
boot::boot.ci(GazYield.boot.bal, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=2)
boot::boot.ci(GazYield.boot.bal, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=3)
boot::boot.ci(GazYield.boot.bal, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=4)
boot::boot.ci(GazYield.boot.bal, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=5)
boot::boot.ci(GazYield.boot.bal, conf = c(0.90,0.95), 
type = c("norm","basic","perc","bca"), index=6)


plsRglm::boxplots.bootpls(GazYield.boot.bal)
plsRglm::confints.bootpls(GazYield.boot.bal)
plsRglm::plots.confints.bootpls(plsRglm::confints.bootpls(GazYield.boot.bal))



plot(GazYield.boot.bal)
boot::jack.after.boot(GazYield.boot.bal, index=1, useJ=TRUE, nt=3)
plot(GazYield.boot.bal,jack=TRUE)


# PLS permutation bootstrap

GazYield.boot.perm <- bootplsbeta(plsRbeta(yield~.,data=GasolineYield,nt=3,
modele="pls-beta"), sim="permutation", stype="i", R=250)
boot::boot.ci(GazYield.boot.perm, conf = c(0.90,0.95), 
type = c("norm","basic","perc"), index=1)
boot::boot.ci(GazYield.boot.perm, conf = c(0.90,0.95), 
type = c("norm","basic","perc"), index=2)
boot::boot.ci(GazYield.boot.perm, conf = c(0.90,0.95), 
type = c("norm","basic","perc"), index=3)
boot::boot.ci(GazYield.boot.perm, conf = c(0.90,0.95), 
type = c("norm","basic","perc"), index=4)
boot::boot.ci(GazYield.boot.perm, conf = c(0.90,0.95), 
type = c("norm","basic","perc"), index=5)
boot::boot.ci(GazYield.boot.perm, conf = c(0.90,0.95), 
type = c("norm","basic","perc"), index=6)
plsRglm::boxplots.bootpls(GazYield.boot.perm)
plot(GazYield.boot.perm)

plsRbeta documentation built on March 31, 2023, 11:01 p.m.