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The field of System Identification (SI) aims to build mathematical models for static and dynamic behavior from experimental data (Ljung, 1987). In particular, nonlinear system identification has become a central issue in the SI community, and from the 1950s onwards many methods have been proposed. In this respect, NARMAX (Nonlinear AutoRegressive Moving Average with eXogenous input) models are among the most well-documented and used model representation of dynamical systems (Billings, 2013).

SysIdentPy: A Python package for System Identification using NARMAX models