Jchemo.jl

Documentation for Jchemo.jl.

Overview

Jchemo provides functions for data exploration and predictions in chemometrics or other domains, with focus on high dimensional data.

The package was initially designed about k-nearest neighbors locally weighted partial least squares regression and discrimination models (kNN-LWPLSR and kNN-LWPLSDA; e.g. https://doi.org/10.1002/cem.3209). It has now been expanded to many other methods for analyzing high dimensional data.

Generic functions such as transform, predict, coef and summary are available. Tuning the predicive models is facilitated by 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).

Some of the functions of Jchemo (in particular the function using kNN selections) use multi-threading to speed the computations. To take advantage of thos, the user has to specify his relevant number of threads (e.g. from the setting menu of the VsCode Julia extension and the file settings.json).

Jchemo uses Makie for plotting. To display the plots, the user has to preliminary install and load one of the Makie's backends (e.g. CairoMakie).

Most of the functions have a help page (each given an example), e.g.:

?savgol