coefs.sgpls.CSim {bootPLS} | R Documentation |
Bootstrap (Y,T) function for plsRglm
A function passed to boot
to perform bootstrap.
Description
Bootstrap (Y,T) function for plsRglm
A function passed to boot
to perform bootstrap.
Usage
coefs.sgpls.CSim(
dataRepYtt,
ind,
nt,
modele,
family = binomial,
maxcoefvalues,
ifbootfail
)
Arguments
dataRepYtt |
Dataset with tt components to resample |
ind |
indices for resampling |
nt |
number of components to use |
modele |
type of modele to use, see plsRglm. Not used, please specify the family instead. |
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 |
ifbootfail |
value to return if the estimation fails on a bootstrap sample |
Value
Numeric vector of the components computed using a bootstrap
resampling or ifbootfail
value if the
bootstrap computation fails.
Author(s)
Jérémy Magnanensi, Frédéric Bertrand
frederic.bertrand@utt.fr
https://fbertran.github.io/homepage/
References
A new bootstrap-based stopping criterion in PLS component construction,
J. Magnanensi, M. Maumy-Bertrand, N. Meyer and F. Bertrand (2016), in The Multiple Facets of Partial Least Squares and Related Methods,
doi: 10.1007/978-3-319-40643-5_18
A new universal resample-stable bootstrap-based stopping criterion for PLS component construction,
J. Magnanensi, F. Bertrand, M. Maumy-Bertrand and N. Meyer, (2017), Statistics and Compututing, 27, 757–774.
doi: 10.1007/s11222-016-9651-4
New developments in Sparse PLS regression, J. Magnanensi, M. Maumy-Bertrand, N. Meyer and F. Bertrand, (2021), Frontiers in Applied Mathematics and Statistics, accepted.
Examples
set.seed(4619)
xran=cbind(rbinom(30,1,.2),matrix(rnorm(150),30,5))
coefs.sgpls.CSim(xran, ind=sample(1:nrow(xran)),
maxcoefvalues=1e5, ifbootfail=rep(NA,3))