coefs.plsRbeta.raw {plsRbeta}

Raw coefficients function for bootstrap techniques

Description

Returns the coefficients of a "plsRbeta" model.

Usage

coefs.plsRbeta.raw(
  dataset,
  ind,
  nt,
  modele,
  family = NULL,
  method = "logistic",
  link = NULL,
  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 bootstrap sample

verbose

should info messages be displayed ?

Value

Coefficients' Estimates on a sample.

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

See also bootplsbeta.

Examples

data("GasolineYield",package="betareg")
bootplsbeta(plsRbeta(yield~.,data=GasolineYield,nt=3, modele="pls-beta"), typeboot="fmodel_par", 
R=250, statistic=coefs.plsRbeta.raw)