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MixedGaussian package

Mixed linear-nonlinear state-space model. The delayed sampling feature of Birch results in a Rao--Blackwellized particle filter with locally-optimal proposal being applied to this model.

The model is detailed in Lindsten and Schön (2010) and was used to demonstrate delayed sampling in Murray et al. (2018).


This package is open source software.

It is licensed under the Apache License, Version 2.0 (the "License"); you may not use it except in compliance with the License. You may obtain a copy of the License at

Getting started

To build, use:

birch build

To run, use:

birch sample --config config/mixed_gaussian.json


  1. F. Lindsten and T. B. Schön (2010). Identification of mixed linear/nonlinear state-space models. In 49th IEEE Conference on Decision and Control (CDC). 6377–6382.

  2. L.M. Murray, D. Lundén, J. Kudlicka, D. Broman and T.B. Schön (2018). Delayed Sampling and Automatic Rao–Blackwellization of Probabilistic Programs. In Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) 2018, Lanzarote, Spain.