rchemo is a package for 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) (e.g. https://doi.org/10.1002/cem.3209). 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).
All the functions have a help page with a documented example.
NOTE: This repository replaces the previous rchemo repository that now is archived.
Click HERE to see what changed in the previous versions.
or write in the R console
news(package = "rchemo")Using Rstudio is recommended for installation and usage.
rchemo can be installed from CRAN, or from Github using the following steps.
Use the Rstudio menu
or write in the R console
install.packages("remotes")a) Most recent version
Write in the R console
remotes::install_github("ChemHouse-group/rchemo", dependencies = TRUE)In case of the following question during installation process:
These packages have more recent versions available.
Which would you like to update?"it is recommended to skip updates (usually choice 3 = None)
b) Any given tagged version
e.g. with tag “v0.1-1”, write in the R console
remotes::install_github("ChemHouse-group/rchemo@v0.1-1", dependencies = TRUE)Write in the R console
library(rchemo)R package rchemo: Dimension Reduction, Regression and Discrimination for Chemometrics. https://github.com/ChemHouse-group/rchemo.