The general linear parametric multivariate modelling concept is presented. This model combines a variety of different kinds of multivariate linear models. The concept of partial spectral analysis is derived from the general model. Some emphasis is laid on the causality demands of the model, and it is shown that the classic strictly-causal structure must be abandoned in order to utilise the modelling in many practical situations. Two special sub-class models are described in detail: the multivariate autoregressive model and the multivariate dynamic adjustment model. Furthermore, time-varying modelling is considered. The modelling of the real system is presented on a general level as a system identification cycle. The application of the methods to real physiological data is presented in the companion paper.
Korhonen, I., Mainardi, L., Loula, P., Garrault, G., Baselli, G., & Bianchi, A. (1996). Linear multivariate models for physiological signal analysis: Theory. Computer Methods and Programs in Biomedicine, 51(1-2), 85-94. https://doi.org/10.1016/0169-2607(96)01764-6