Pymob documentation

Pymob is a Python based model building platform. It automates repetitive tasks in the modeling process so that you can focus on building models, asking questions to the real world and learn from observations.

The idea of pymob originated from the frustration with fitting complex models to complicated datasets (missing observations, non-uniform data structure, non-linear models, ODE models). In such scenarios a lot of time is spent matching observations with model results.

Usually, parameter estimation/optimization/inference algorithms have dedicated requirements for how to input data and specify parameters. This produces a significant barrier to explore different, potentially better suited algorithms to estimate the data.

The main goals of pymob are

• providing a uniform interface for describing models

• using this interface to fit models to data with a variety of optimization and inference algorithms

• enabling reproducibility by versioning case studies and distributing them as python packages

Next steps

Contents

• User Guide
• Examples
• API reference