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Collection of linear & nonlinear (Kalman) Filters for economic DSGE models
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EconSieve - Kalman Filter, Unscented Kalman filter, Ensemble Filter and Iterative Path-Adjusting Smoother (IPAS)

Apart from the smoother, I literally stole most of the code from these two projects:


They deserve most of the merits. I just made everything look way more complicated. Sometimes filterpy was more efficient, sometimes pykalman. Unfortunately the pykalman project is orphaned. I tweaked something here and there:

  • treating numerical errors in the UKF covariance matrix by looking for the nearest positive semi-definite matrix
  • eliminating identical sigma points (yields speedup assuming that evaluation of each point is costly)
  • extracting functions from classes and compile them using the @njit flag (speedup)
  • major cleanup

IPAS is build from scratch. I barely did any testing as a standalone filter but always used it in combination with the 'pydsge' API, where it works very well.

Yet I have not updated the documentation or the licensing.

Installation with pip (simple)

The simplest way is to clone the repository and then from within the cloned folder run (Windows user from the Anaconda Prompt):

pip3 install .

Installation with pip (elegant via git)

The handy way is to first install git. Linux users just use their respective repos. Windows users get it here:

pip3 install git+
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