Multiregression Dynamic Models
Catriona M. Queen, Jim Q. Smith · Journal of the Royal Statistical Society Series B (Statistical Methodology) · 1993
SUMMARY Multiregression dynamic models are defined to preserve certain conditional independence structures over time across a multivariate time series. They are non-Gaussian and yet they can often be updated in closed form. The first two moments of their one-step-ahead forecast distribution can be easily calculated. Furthermore, they can be built to contain all the features of the univariate dynamic linear model and promise more efficient identification of causal structures in a time series than has been possible in the past.