plsRbeta (version 0.2.6)

bootplsbeta: 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 = coefs.plsRbeta,
  sim = "ordinary",
  stype = "i",
  ...
)

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).

…

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.

Value

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

Details

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

References

Fr<U+00E9>d<U+00E9>ric Bertrand, Nicolas Meyer, Mich<U+00E8>le Beau-Faller, Karim El Bayed, Izzie-Jacques Namer, Myriam Maumy-Bertrand (2013). R<U+00E9>gression B<U+00EA>ta PLS. Journal de la Soci<U+00E9>t<U+00E9> Fran<U+00E7>aise de Statistique, 154(3):143-159. http://publications-sfds.math.cnrs.fr/index.php/J-SFdS/article/view/215

See Also

boot

Examples

# NOT RUN {
data("GasolineYield",package="betareg")

GazYield.boot <- bootplsbeta(plsRbeta(yield~.,data=GasolineYield,nt=3,
modele="pls-beta"), 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))


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

# PLS bootstrap balanced

GazYield.boot <- bootplsbeta(plsRbeta(yield~.,data=GasolineYield,nt=3,
modele="pls-beta"), sim="balanced", 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))



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


# PLS permutation bootstrap

GazYield.boot <- bootplsbeta(plsRbeta(yield~.,data=GasolineYield,nt=3,
modele="pls-beta"), sim="permutation", stype="i", R=250)
boot::boot.ci(GazYield.boot, conf = c(0.90,0.95), type = c("norm","basic","perc"), index=1)
boot::boot.ci(GazYield.boot, conf = c(0.90,0.95), type = c("norm","basic","perc"), index=2)
boot::boot.ci(GazYield.boot, conf = c(0.90,0.95), type = c("norm","basic","perc"), index=3)
boot::boot.ci(GazYield.boot, conf = c(0.90,0.95), type = c("norm","basic","perc"), index=4)
boot::boot.ci(GazYield.boot, conf = c(0.90,0.95), type = c("norm","basic","perc"), index=5)
boot::boot.ci(GazYield.boot, conf = c(0.90,0.95), type = c("norm","basic","perc"), index=6)
plsRglm::boxplots.bootpls(GazYield.boot)
plot(GazYield.boot)
# }
# NOT RUN {
# }