Package: rchemo
Type: Package
Title: Dimension Reduction, Regression and Discrimination for
        Chemometrics
Version: 0.1-4
Authors@R: c(
    person("Marion", "Brandolini-Bunlon", email = "marion.brandolini-bunlon@inrae.fr", role = c("aut", "cre")),
    person("Benoit", "Jaillais", email = "benoit.jaillais@inrae.fr", role = c("aut")),
    person("Jean-Michel", "Roger", email = "jean-michel.roger@inrae.fr", role = c("aut")),
    person("Matthieu", "Lesnoff", email = "matthieu.lesnoff@cirad.fr", role = c("aut")))
Description: Data exploration and prediction with focus on high
        dimensional data and chemometrics. The package was initially
        designed about partial least squares regression and
        discrimination models and variants, in particular locally
        weighted PLS models (LWPLS). Then, it has been expanded to many
        other methods for analyzing high dimensional data. The name
        'rchemo' comes from the fact that the package is orientated to
        chemometrics, but most of the provided methods are fully
        generic to other domains. Functions such as transform(),
        predict(), coef() and summary() are available. Tuning the
        predictive models is facilitated by generic functions
        gridscore() (validation dataset) and gridcv()
        (cross-validation). Faster versions are also available for
        models based on latent variables (LVs) (gridscorelv() and
        gridcvlv()) and ridge regularization (gridscorelb() and
        gridcvlb()).
Imports: stats, graphics, grDevices, data.table, FNN, signal, e1071,
        utils
Depends: R (>= 4.0)
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
URL: https://github.com/ChemHouse-group/rchemo/
License: GPL-3
LazyData: yes
NeedsCompilation: no
Packaged: 2026-06-30 19:30:10 UTC; root
Author: Marion Brandolini-Bunlon [aut, cre], Benoit Jaillais [aut],
        Jean-Michel Roger [aut], Matthieu Lesnoff [aut]
Maintainer: Marion Brandolini-Bunlon
 <marion.brandolini-bunlon@inrae.fr>
Repository: https://cran.r-universe.dev
Date/Publication: 2026-06-30 16:00:07 UTC
RemoteUrl: https://github.com/cran/rchemo
RemoteRef: HEAD
RemoteSha: 635857048e27ac266306df9a716a274b3cf237da