The linear process mixture model
Jason A. Palmer, Kenneth Kreutz-Delgado, Scott Makeig · 2013
We consider a likelihood framework for analyzing multivariate time series as mixtures of independent linear processes. We propose a flexible, Newton algorithm for estimating impulse response functions associated with independent linear processes and an EM-based finite mixture model to handle intermittent regimes. Simulations and application to EEG are also provided.