petab-select 0.2.1

PEtab Select: an extension to PEtab for model selection.

The repository for the development of the extension to PEtab for model selection, including the additional file formats and Python 3 package.

Install

The Python 3 package 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 for usage of PEtab Select with

• the command-line interface, and
• the Python 3 interface,

in the doc/examples directory.

Supported features

Criterion

• AIC: https://en.wikipedia.org/wiki/Akaike_information_criterion#Definition
• AICc: https://en.wikipedia.org/wiki/Akaike_information_criterion#Modification_for_small_sample_size
• BIC: https://en.wikipedia.org/wiki/Bayesian_information_criterion#Definition

Methods

• forward: https://en.wikipedia.org/wiki/Stepwise_regression#Main_approaches
• backward: https://en.wikipedia.org/wiki/Stepwise_regression#Main_approaches
• brute_force: Optimize all possible model candidates, then return the model with the best criterion value.
• famos: https://doi.org/10.1371/journal.pcbi.1007230

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.