PyFlux is an open source time series library for the Python programming language. Built upon the NumPy/SciPy/Pandas libraries, PyFlux allows for easy application of a vast array of time series methods and inference capabilities.

See some examples and documentation at PyFlux.com. Or see worked-through examples in this talk given to the PyData London Meetup in June 2016.

• ARIMA models
• ARIMAX models
• GARCH models
• Beta-t-EGARCH models
• EGARCH-in-mean models
• EGARCH-in-mean regression models
• Skew-t-EGARCH models
• Skew-t-EGARCH-in-mean models
• GAS models
• GAS State Space models
• GP-NARX models
• Gaussian State Space models
• Non-Gaussian State Space models
• VAR models
• Bayesian VAR models

• Black Box Variational Inference
• Laplace Approximation
• Maximum Likelihood and Penalized Maximum Likelihood
• Metropolis-Hastings

pip install pyflux

Supported on Python 2.7 and 3.5.

PyFlux is still alpha software so results should be treated with care, but citations are very welcome:

Ross Taylor. 2016. PyFlux: An open source time series library for Python http://www.pyflux.com