rchemo
Dimension Reduction, Regression and Discrimination for Chemometrics
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()).
- Version0.1-3
- R version≥ 4.0
- LicenseGPL-3
- Needs compilation?No
- Last release09/11/2024
Documentation
Team
Marion Brandolini-Bunlon
Matthieu Lesnoff
Show author detailsRolesAuthorBenoit Jaillais
Show author detailsRolesAuthorJean-Michel Roger
Show author detailsRolesAuthor
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports4 packages
- Suggests2 packages