Multiregression dynamic models

Multiregression dynamic models are defined to preserve certain conditional independence structures over time across a multivariate the 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 tie 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

[1]  A. Dawid.  Conditional Independence in Statistical Theory , 1979 .

[2]  M. Priestley.  STATE‐DEPENDENT MODELS: A GENERAL APPROACH TO NON‐LINEAR TIME SERIES ANALYSIS , 1980 .

[3]  A. Zellner,et al.  Basic Issues in Econometrics. , 1986 .

[4]  M. West,et al.  Dynamic Generalized Linear Models and Bayesian Forecasting , 1985 .

[5]  Ross D. Shachter.  Intelligent Probabilistic Inference , 1985, UAI.

[6]  Jean-Pierre Florens,et al.  A Linear-theory for Noncausality , 1985 .

[7]  A. Harvey.  Analysis and generalisation of a multivariate exponential smoothing model , 1986 .

[8]  P. Holland.  Statistics and Causal Inference , 1985 .

[9]  G. Kitagawa.  Non-Gaussian State—Space Modeling of Nonstationary Time Series , 1987 .

[10]  M. West,et al.  An analysis of international exchange rates using multivariate DLM's , 1987 .

[11]  Judea Pearl,et al.  The Logic of Representing Dependencies by Directed Graphs , 1987, AAAI.

[12]  M. West,et al.  Bayesian forecasting and dynamic models , 1989 .

[13]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[14]  S. Lauritzen,et al.  Mixed graphical association models; discussions and reply , 1989 .

[15]  J. Q. Smith.  Influence Diagrams for Statistical Modelling , 1989 .

[16]  Michael A. West,et al.  Efficient bayesian learning in non‐linear dynamic models , 1990 .

[17]  Andrew Harvey,et al.  Forecasting, Structural Time Series Models and the Kalman Filter , 1990 .

[18]  N. Wermuth,et al.  On Substantive Research Hypotheses, Conditional Independence Graphs and Graphical Chain Models , 1990 .

[19]  Steffen L. Lauritzen,et al.  Independence properties of directed markov fields , 1990, Networks.

[20]  Catriona M. Queen.  Using the Multiregression Dynamic Model to Forecast Brand Sales in a Competitive Product Market , 1994 .