The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

packMBPLSDA: Multi-Block Partial Least Squares Discriminant Analysis

Several functions are provided to implement a MBPLSDA : components search, optimal model components number search, optimal model validity test by permutation tests, observed values evaluation of optimal model parameters and predicted categories, bootstrap values evaluation of optimal model parameters and predicted cross-validated categories. The use of this package is described in Brandolini-Bunlon et al (2019. Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data. Metabolomics, 15(10):134).

Version: 0.9.0
Depends: ade4, pROC
Imports: MASS, parallel, doParallel, foreach, FactoMineR
Published: 2022-06-20
DOI: 10.32614/CRAN.package.packMBPLSDA
Author: Marion Brandolini-Bunlon, Stephanie Bougeard, Melanie Petera, Estelle Pujos-Guillot
Maintainer: Marion Brandolini-Bunlon <marion.brandolini-bunlon at inra.fr>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
NeedsCompilation: no
In views: Omics
CRAN checks: packMBPLSDA results

Documentation:

Reference manual: packMBPLSDA.pdf

Downloads:

Package source: packMBPLSDA_0.9.0.tar.gz
Windows binaries: r-devel: packMBPLSDA_0.9.0.zip, r-release: packMBPLSDA_0.9.0.zip, r-oldrel: packMBPLSDA_0.9.0.zip
macOS binaries: r-release (arm64): packMBPLSDA_0.9.0.tgz, r-oldrel (arm64): packMBPLSDA_0.9.0.tgz, r-release (x86_64): packMBPLSDA_0.9.0.tgz, r-oldrel (x86_64): packMBPLSDA_0.9.0.tgz
Old sources: packMBPLSDA archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=packMBPLSDA 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.
Health stats visible at Monitor.