Coefficients function for permutation bootstrap techniques

A function passed to boot to perform bootstrap.

Usage

permcoefs.plsRbeta(
  dataset,
  ind,
  nt,
  modele,
  family = NULL,
  method = "logistic",
  link = "logit",
  link.phi = NULL,
  type = "ML",
  maxcoefvalues,
  ifbootfail,
  verbose = TRUE
)

Arguments

dataset: dataset to resample
ind: indices for resampling
nt: number of components to use
modele: name of the PLS glm or PLS beta model to be fitted ("pls", "pls-glm-Gamma", "pls-glm-gaussian", "pls-glm-inverse.gaussian", "pls-glm-logistic", "pls-glm-poisson", "pls-glm-polr", "pls-beta"). Use "modele=pls-glm-family" to enable the family option.
family: family to use if GLM model, see plsRbeta
method: method for beta regression
link: link for beta regression
link.phi: link.phi for beta regression
type: type of estimates
maxcoefvalues: maximum values allowed for the estimates of the coefficients to discard those coming from singular bootstrap samples
ifbootfail: value to return if the estimation fails on a
verbose: should info messages be displayed ?

Value

Estimates on a bootstrap sample.

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. https://ojs-test.apps.ocp.math.cnrs.fr/index.php/J-SFdS/article/view/215

Author

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

Examples

# \donttest{
data("GasolineYield",package="betareg")

GazYield.boot <- bootplsbeta(plsRbeta(yield~.,data=GasolineYield,nt=3,
modele="pls-beta", verbose=FALSE), sim="ordinary", stype="i", R=250, statistic=permcoefs.plsRbeta)
# }