Implementation of N4SID, Kalman filtering and state-space models
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].
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 is provided here. An example Jupyter notebook is provided here.