permcoefs.plsRglmnp: Coefficients for permutation bootstrap computations of PLSGLR...

In plsRglm: Partial Least Squares Regression for Generalized Linear Models

Coefficients for permutation bootstrap computations of PLSGLR models

Description

A function passed to boot to perform bootstrap.

Usage

permcoefs.plsRglmnp(
  dataRepYtt,
  ind,
  nt,
  modele,
  family = NULL,
  maxcoefvalues,
  wwetoile,
  ifbootfail
)

Arguments

dataRepYtt	components' coordinates to bootstrap
ind	indices for resampling
nt	number of components to use
modele	type of modele to use, see plsRglm
family	glm family to use, see plsRglm
maxcoefvalues	maximum values allowed for the estimates of the coefficients to discard those coming from singular bootstrap samples
wwetoile	values of the Wstar matrix in the original fit
ifbootfail	value to return if the estimation fails on a bootstrap sample

Value

estimates on a bootstrap sample or ifbootfail value if the bootstrap computation fails.

Note

~~some notes~~

Author(s)

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

See Also

See also bootplsglm

Examples

data(Cornell)

# (Y,X) bootstrap of a PLSGLR model
# statistic=coefs.plsRglm is the default for (Y,X) bootstrap of a PLSGLR models.
set.seed(250)
modplsglm <- plsRglm(Y~.,data=Cornell,1,modele="pls-glm-family",family=gaussian)
Cornell.bootYT <- bootplsglm(modplsglm, R=250, statistic=permcoefs.plsRglmnp, verbose=FALSE)

plsRglm documentation built on March 31, 2023, 11:10 p.m.