Provides tools for Bayesian parameter estimation of adsorption isotherm models using Markov Chain Monte Carlo (MCMC) methods.
This package enables users to fit non-linear and linear adsorption isotherm models—Freundlich, Langmuir, and Temkin—within a
probabilistic framework, capturing uncertainty and parameter correlations. It provides posterior summaries, 95% credible intervals,
convergence diagnostics (Gelman-Rubin), and visualizations through trace and density plots. With this R package, researchers can
rigorously analyze adsorption behavior in environmental and chemical systems using robust Bayesian inference. For more details,
see Gilks et al. (1995)