The Multiparameter Steady Model
Journal of the Royal Statistical Society: Series B (Statistical Methodology) · 1981 · Volume 43 · Issue 2
DOI: 10.1111/j.2517-6161.1981.tb01178.x
Abstract
This paper generalizes and extends the idea of a steady evolution of a time series to multiparameter processes with any observational distribution. Particular examples of such processes are given. These include the multivariate steady process, univariate normal processes where the observational variance is unknown and series of multinomial observations with a steady model on the cell probabilities.
Keywords
bayesian forecasting, multivariate forecasting, steady models, dynamic linear model, exponential weighted moving averages
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