Bootstrap Hyperparameter Selection for PLS Models and Extensions
Overview
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', doi:10.3389/fams.2021.693126).
- Update links to canonical form
- Added compatibility guard for plsRglm bootstrap confidence interval shapes
From NEWS.md in the release
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- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
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- ERROR12 OK, 1 ERROR2026-06-08
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- ERROR13 OK, 1 ERROR2026-04-24
- OK14 OK2026-03-10
Documentation
- Help pages
- 18 (2 internal)includes a package overview page
- Examples that run
- 94%15 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 97%
- Return-value docs
- 100%
- Help pages citing references
- 94%
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Checks run against github.com/fbertran/bootpls on 2026-10-25.
The R CMD check workflow runs on macOS
GitHub Pages site last deployed 2025-09-24
pkgdown site last built 2025-09-09, before release 1.2.0 (2026-06-08)
Dependencies
Code & Tests
Datasets
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Package metadata
- First published
- 2021-07-15
- Total releases
- 4 / 5 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 13 KB / 1 file
- Download size
- 96 KB
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