Contribution Guidelines

In its short life so far, PyFlux has been a personal project of mine (@RJT1990), but I would now like to be more forthright and welcoming of community contributions. In particular, contributions that achieve the following are very much needed:

• Contributions that improve estimation of models - in particular, better starting values, or a pre-optimization stage that finds good starting values for model fitting.

• Contributions that improve performance - for example, further Cythonization, or more basic optimizations that might be lurking in the code in some places.

• Contributions that expand the feature set - for example, new distributions for GAS models, or new model types in their entirety.

Because this is a new project, my suggested guidelines for contributions are extremely liberal, but the following things are desirable:

• Please write unit tests for new features.
• Please ensure the API is kept as consistent as possible across model types; this is one of the plus points about the library so far.
• If you are adding a new feature, then please amend documentation (or write new documentation to accompany the feature).
• New model types that are amenable to multiple types of estimation are to be preferred over those that require very specific estimation procedures.

Thanks!

Ross