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Variance estimation for multivariate dynamic linear models
Authors:Emanuel Barbosa  Jeff Harrison
Abstract:The problem of estimating unknown observational variances in multivariate dynamic linear models is considered. Conjugate procedures are possible for univariate models and also for special very restrictive common components models but they are not generally applicable. However, for clarity of operation and in order to avoid numerical integration, it is desirable to have conjugacy or approximate conjugacy. Such an approximate procedure is proposed based upon a simple analytic approximation. It is exact for the sub-class of conjugate models and improves on a previous procedure based upon the Robust filter.
Keywords:Bayesian forecasting  Dynamic linear model  Multivariate time series  Robust filter  Variance estimation
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