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bootPLS: Bootstrap Hyperparameter Selection for PLS Models and Extensions

Several implementations of non-parametric stable bootstrap-based techniques to determine the numbers of components for Partial Least Squares linear or generalized linear regression models as well as and sparse Partial Least Squares linear or generalized linear regression models. The package collects techniques that were published in a book chapter (Magnanensi et al. 2016, 'The Multiple Facets of Partial Least Squares and Related Methods', <doi:10.1007/978-3-319-40643-5_18>) and two articles (Magnanensi et al. 2017, 'Statistics and Computing', <doi:10.1007/s11222-016-9651-4>) and (Magnanensi et al. 2021, 'Frontiers in Applied Mathematics and Statistics', accepted.).

Version: 0.9.9
Depends: R (≥ 3.5.0)
Imports: boot, doParallel, foreach, plsRglm, pls, spls, bipartite, mvtnorm
Suggests: knitr, markdown, plsdof, prettydoc, rmarkdown
Published: 2021-07-15
Author: Frederic Bertrand ORCID iD [cre, aut], Jeremy Magnanensi [aut], Myriam Maumy-Bertrand ORCID iD [aut]
Maintainer: Frederic Bertrand <frederic.bertrand at utt.fr>
BugReports: https://github.com/fbertran/bootPLS/issues/
License: GPL-3
URL: https://fbertran.github.io/bootPLS/, https://github.com/fbertran/bootPLS/
NeedsCompilation: no
Classification/MSC: 62N01, 62N02, 62N03, 62N99
Citation: bootPLS citation info
Materials: README NEWS
CRAN checks: bootPLS results

Documentation:

Reference manual: bootPLS.pdf
Vignettes: Selecting the number of components

Downloads:

Package source: bootPLS_0.9.9.tar.gz
Windows binaries: r-devel: bootPLS_0.9.9.zip, r-release: bootPLS_0.9.9.zip, r-oldrel: bootPLS_0.9.9.zip
macOS binaries: r-release (arm64): bootPLS_0.9.9.tgz, r-oldrel (arm64): bootPLS_0.9.9.tgz, r-release (x86_64): bootPLS_0.9.9.tgz, r-oldrel (x86_64): bootPLS_0.9.9.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=bootPLS to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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