View source: R/tilt.bootplsbeta.R
tilt.bootplsbeta | R Documentation |
Provides a wrapper for the bootstrap function tilt.boot
from the
boot
R package.
Implements non-parametric tilted bootstrap for PLS
beta regression models by case resampling : the tilt.boot
function
will run an initial bootstrap with equal resampling probabilities (if
required) and will use the output of the initial run to find resampling
probabilities which put the value of the statistic at required values. It
then runs an importance resampling bootstrap using the calculated
probabilities as the resampling distribution.
tilt.bootplsbeta(
object,
typeboot = "plsmodel",
statistic = coefs.plsRbeta,
R = c(499, 250, 250),
alpha = c(0.025, 0.975),
sim = "ordinary",
stype = "i",
index = 1,
stabvalue = 1e+06
)
object |
An object of class |
typeboot |
The type of bootstrap. Either (Y,X) boostrap
( |
statistic |
A function which when applied to data returns a vector
containing the statistic(s) of interest. |
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 |
alpha |
The alpha level to which tilting is required. This parameter is
ignored if |
sim |
A character string indicating the type of simulation required.
Possible values are |
stype |
A character string indicating what the second argument of
|
index |
The index of the statistic of interest in the output from
|
stabvalue |
A value to hard threshold bootstrap estimates computed from atypical resamplings. |
An object of class "boot".
Frédéric Bertrand
frederic.bertrand@utt.fr
https://fbertran.github.io/homepage/
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
tilt.boot
data("GasolineYield",package="betareg")
yGasolineYield <- GasolineYield$yield
XGasolineYield <- GasolineYield[,2:5]
modplsRbeta <- plsRbeta(yGasolineYield, XGasolineYield, nt=3,
modele="pls-beta")
# GazYield.tilt.boot <- tilt.bootplsbeta(modplsRbeta,
# statistic=coefs.plsRbeta, R=c(499, 100, 100),
# alpha=c(0.025, 0.975), sim="balanced", stype="i", index=1)
# boxplots.bootpls(GazYield.tilt.boot,1:2)
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