Provides cross-validation tools for adsorption isotherm models, supporting both linear and non-linear forms.
Current methods cover commonly used isotherms including the Freundlich, Langmuir, and Temkin models.
This package implements K-fold and leave-one-out cross-validation (LOOCV) with optional clustering-based
fold assignment to preserve underlying data structures during validation. Model predictive performance is assessed
using mean squared error (MSE), with optional graphical visualization of fold-wise MSEs to support intuitive evaluation of model accuracy.
This package is intended to facilitate rigorous model validation in adsorption studies and aid researchers in selecting robust isotherm models.
For more details, see Montgomery et al. (2012)