Statistical Estimation and Classification Algorithms for Regime-Switching VAR Model with Exogenous Variables

Vladimir Malugin, Alexander Novopoltsev


We consider a vector autoregression model with exogenous variables and Markov-switching regimes to describe complex systems with cyclic changes of states. To estimate and forecast the states, we propose EM and discriminant analysis algorithms based on non-classified and classified data samples accordingly. The accuracy of the algorithms is examined by means of computer simulation experiments.

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