Data, software and scripts related to the Process PLS methodology manuscript
Description
Process PLS repository including software implentations, data and scripts. Repository contains: - R package pathmodelr (See README.txt for installation guide) (GPLv3) - Matlab library - Link to Python implementation (here: https://doi.org/10.5281/zenodo.7074754) - Simulated data of a crude oil distillation process (with scripts to reproduce the results) (CC-BY) - R code for the Val de Loire wine tasting analysis (CC-BY) New in v2: PDF with helpfile to understand the model output New in v4: Matlab implementation New in v8: - Val de Loir analysis file includes function to rename the Process PLS output in R and a function to provide the outer-model R2 values of each block in a simple manner. Also added the renaming function separately to 'software folder' New in V9: - Python Implementation (link: https://doi.org/10.5281/zenodo.7074754) Process PLS is a path modelling algorithm for multiblock data. First described in: van Kollenburg et al. Process PLS: Incorporating substantive knowledge into the predictive modelling of multiblock, multistep, multidimensional and multicollinear process data" https://doi.org/10.1016/j.compchemeng.2021.107466
Files
Steps to reproduce
Analysis of the Val de Loire data can be directly run and replicated