Classical Model Fitting of Adsorption Isotherms
Overview
Provides tools for classical parameter estimation of adsorption isotherm models, including both linear and nonlinear forms of the Freundlich, Langmuir, and Temkin isotherms. This package allows users to fit these models to experimental data, providing parameter estimates along with fit statistics such as Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Error metrics are computed to evaluate model performance, and the package produces model fit plots with bootstrapped 95% confidence intervals. Additionally, it generates residual plots for diagnostic assessment of the models. Researchers and engineers in material science, environmental engineering, and chemical engineering can rigorously analyze adsorption behavior in their systems using this straightforward, non-Bayesian approach. For more details, see Harding (1907) doi:10.2307/2987516.
Install
Health
NOTERd contentsr-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc
Rd files without \usage: ‘fit_freundlichLM.Rd’ ‘fit_freundlichNLM.Rd’ ‘fit_langmuirLM1.Rd’ ‘fit_langmuirLM2.Rd’ ‘fit_langmuirLM3.Rd’ ‘fit_langmuirLM4.Rd’ ‘fit_langmuirNLM.Rd’ ‘fit_temkinLM.Rd’ ‘fit_temkinNLM.Rd’ \arguments should not be documented without \usage.
- NOTE11 OK, 2 NOTENow
- NOTE12 OK, 1 NOTE2026-07-11
- OK14 OK2026-03-10
Documentation
- Help pages
- 9
- Examples that run
- 100%9 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- not tracked
- Return-value docs
- 100%
- Help pages citing references
- 100%
Downloads
Dependencies
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- 0.1.1Latest
- 0.1.02025-06-05
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-06-05
- Total releases
- 2 / 1 yrs
- License
- GPL-3 OSI
- Download size
- 10 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("adsoRptionCMF")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.