petab-select 0.3.4

PEtab Select: an extension to PEtab for model selection.

The PEtab extension for model selection, including the additional file formats and package.

Install

The Python 3 library provides both the Python 3 and command-line (CLI) interfaces, and can be installed from PyPI, with pip3 install petab-select.

Documentation

Further documentation is available at http://petab-select.readthedocs.io/.

Examples

There are example Jupyter notebooks covering visualization, custom non-SBML models, and the CLI and Python API, in the doc/examples directory. The notebooks can be viewed at https://petab-select.readthedocs.io/en/stable/examples.html.

Supported features

PEtab Select offers various methods and criteria for model selection, as well as a variety of visualization options.

Criteria

• AIC: Akaike information criterion
• AICc: Corrected Akaike information criterion
• BIC: Bayesian information criterion

Methods

• forward: Forward selection. Iteratively increase model complexity.
• backward: Backward selection. Iteratively decrease model complexity.
• brute_force. Calibrate all models.
• famos: Flexible and dynamic Algorithm for Model Selection (FAMoS)

Note that the directional methods (forward, backward) find models with the smallest step size (in terms of number of estimated parameters). For example, given the forward method and a predecessor model with 2 estimated parameters, if there are no models with 3 estimated parameters, but some models with 4 estimated parameters, then the search may return candidate models with 4 estimated parameters.