The goal is infer parameters in a model that can predict future output, given new input. We are testing the following models:

• Nonlinear AutoRegressive model with eXogenous input (NARX; see ForneyLab node code)
• Nonlinear AutoRegressive Moving Average model with eXogenous input (NARMAX; see ForneyLab node code)

These models are standard in the control systems community. Typically, (recursive) least-squares or some other form of frequentist estimation is used. In this repo, we employ Free Energy Minimisation.

We run a series of verification experiments and a validation experiment on the Silverbox data set from the Nonlinear Benchmark.

Questions, comments and general feedback can be directed to the issues tracker.