permcoefs.plsRnp: Coefficients computation for permutation bootstrap

In plsRglm: Partial Least Squares Regression for Generalized Linear Models

Coefficients computation for permutation bootstrap

Description

A function passed to boot to perform bootstrap.

Usage

permcoefs.plsRnp(
  dataRepYtt,
  ind,
  nt,
  modele,
  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
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.

Author(s)

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

See Also

See also bootpls

Examples

data(Cornell)
XCornell<-Cornell[,1:7]
yCornell<-Cornell[,8]

# Lazraq-Cleroux PLS (Y,X) bootstrap
# statistic=coefs.plsR is the default for (Y,X) resampling of PLSR models.
set.seed(250)
modpls <- plsR(yCornell,XCornell,1)
Cornell.bootYT <- bootpls(modpls, R=250, typeboot="fmodel_np", sim="permutation",
statistic=permcoefs.plsRnp, verbose=FALSE)

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