Implementation of N4SID, Kalman filtering and state-space models
Project description
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)-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].
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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