adsoRptionMCMC: Bayesian Estimation of Adsorption Isotherms via MCMC

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) <doi:10.1201/b14835>, and Gamerman & Lopes (2006) <doi:10.1201/9781482296426>.

Version:	0.1.0
Imports:	MCMCpack, coda, stats, graphics
Suggests:	testthat
Published:	2025-05-30
DOI:	10.32614/CRAN.package.adsoRptionMCMC
Author:	Paul Angelo C. Manlapaz [aut, cre]
Maintainer:	Paul Angelo C. Manlapaz <pacmanlapaz at gmail.com>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	adsoRptionMCMC results

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