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- W2051227245 abstract "Many time series are weighted sums of component time series. If the same dynamic linear model generates all of the component time series, it also generates the linearly aggregated time series. This paper establishes the result that if the prior distribution of the dynamic parameter estimators is the same for the dynamic linear model applied to the linearly aggregated time series as for the weighted sum of the component dynamic linear model estimators, the posterior covariance matrix for the linearly aggregated model estimators equals the posterior covariance matrix for the weighted sum of the component model estimators plus the weighted sum of the covariance matrices of the posterior mean vectors averaged over all possible component observations such that the weighted sum is the linearly aggregated observation. This paper determines the relative efficiency of the two estimators and shows that the generalized variance of the posterior estimators for the linearly aggregated model is always greater than or equal to the generalized variance of the weighted sum of component posterior estimators." @default.
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- W2051227245 date "1990-01-01" @default.
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- W2051227245 title "The efficiency of dynamic linear model estimators applied to a linearly aggregated time series" @default.
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- W2051227245 doi "https://doi.org/10.1080/03610929008830188" @default.
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