CoMSES Net maintains cyberinfrastructure to foster FAIR data principles for access to and (re)use of computational models. Model authors can publish their model code in the Computational Model Library with documentation, metadata, and data dependencies and support these FAIR data principles as well as best practices for software citation. Model authors can also request that their model code be peer reviewed to receive a DOI. All users of models published in the library must cite model authors when they use and benefit from their code.
Please check out our model archive tutorial or contact us if you have any questions or concerns about archiving your model.
CoMSES Net also maintains a curated database of over 7500 publications of agent-based and individual based models with additional metadata on availability of code and bibliometric information on the landscape of ABM/IBM publications that we welcome you to explore.
This Python module contain a function that is able to test the ergodicity of a given agent based model. It is sufficient to produce one long time series and many smaller time series. The function uses
This is a stationarity test, it tests whether a given moment is constant during the time series (null hypothesis). The Wald Wolfowitz nonparametric fitness test is applied to time series.