Parallel and distributed computational multivariate time series modeling in the state space
Celso Pascoli Bottura, Gilmar Barreto, Maurício José Bordon, Annabell Del Real Tamariz · 2002
In this paper a parallel and distributed computational procedure using a subspace method developed by Aoki (1990) for state space modeling of multivariate time series is proposed and implemented. The parallel solution of the Riccati equation due to the large computational effort it requires receives a special attention. For model evaluation, short time predictions, where a central role is played by a Kalman filtering approach are tested and some results are presented.