If you would like to use our software, please cite it using the following:
Iwanaga, T., Usher, W., & Herman, J. (2022). Toward SALib 2.0: Advancing the accessibility and interpretability of global sensitivity analyses. Socio-Environmental Systems Modelling, 4, 18155. doi:10.18174/sesmo.18155
Herman, J. and Usher, W. (2017) SALib: An open-source Python library for sensitivity analysis. Journal of Open Source Software, 2(9). doi:10.21105/joss.00097
If you use BibTeX, cite using the following entries:
@article{Iwanaga2022, title = {Toward {SALib} 2.0: {Advancing} the accessibility and interpretability of global sensitivity analyses}, volume = {4}, url = {https://sesmo.org/article/view/18155}, doi = {10.18174/sesmo.18155}, journal = {Socio-Environmental Systems Modelling}, author = {Iwanaga, Takuya and Usher, William and Herman, Jonathan}, month = may, year = {2022}, pages = {18155}, } @article{Herman2017, doi = {10.21105/joss.00097}, url = {https://doi.org/10.21105/joss.00097}, year = {2017}, month = {jan}, publisher = {The Open Journal}, volume = {2}, number = {9}, author = {Jon Herman and Will Usher}, title = {{SALib}: An open-source Python library for Sensitivity Analysis}, journal = {The Journal of Open Source Software} }
Many projects now use the Global Sensitivity Analysis features provided by SALib. Here is a selection:
- The City Energy Analyst
- pynoddy
- savvy
- rhodium
- pySur
- EMA workbench
- Brain/Circulation Model Developer
- DAE Tools
- agentpy
- uncertainpy
- CLIMADA
- Sensitivity Analyis in Python
- Sensitivity Analysis with SALib
- Running Sobol using SALib
- Extensions of SALib for more complex sensitivity analyses
If you would like to be added to this list, please submit a pull request, or create an issue.
Many thanks for using SALib.