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NFourSID

Implementation of the N4SID algorithm for subspace identification [1], together with Kalman filtering and state-space
models.

State-space models are versatile models for representing multi-dimensional timeseries.
As an example, the ARMAX(p, q, r)-models - AutoRegressive MovingAverage with eXogenous input -
are included in the representation of state-space models.
By extension, ARMA-, AR- and MA-models can be described, too.
The numerical implementations are based on [2].

Installation

Releases are made available on PyPi.
The recommended installation method is via pip:

pip install nfoursid

For a development setup, the requirements are in dev-requirements.txt.
Subsequently, this repo can be locally pip-installed.

Documentation and code example

Documentation is provided here.
An example Jupyter notebook is provided here.

References

Van Overschee, Peter, and Bart De Moor. "N4SID: Subspace algorithms for the identification of combined
deterministic-stochastic systems." Automatica 30.1 (1994): 75-93.
Verhaegen, Michel, and Vincent Verdult. Filtering and system identification: a least squares approach.
Cambridge university press, 2007.

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Dependencies of nfoursid (3).
Dependency	Optional
matplotlib	false
numpy	false
pandas	false

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nfoursid

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