MCMC System Identification

Markov Chain Monte-Carlo methods are used to calculate probability density functions for parameters in dynamic systems models. By virtue of computation of the true posterior density, these methods allow accurate quantification of estimation error, even for short data lengths.

System Identification Toolbox

This toolbox is a MATLAB-based software package for the estimation of dynamic systems. A wide range of standard estimation approaches are supported. These include the use of non-parametric, subspace-based and prediction-error algorithms coupled (in the latter case) with either MIMO state space or MISO polynomial model structures.