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• W2125804932 abstract "Bayesian inference is developed for matrix-variate dynamic linear models (MV-DLMs), in order to allow missing observation analysis, of any sub-vector or sub-matrix of the observation time series matrix. We propose modifications of the inverted Wishart and matrix t distributions, replacing the scalar degrees of freedom by a diagonal matrix of degrees of freedom. The MV-DLM is then re-defined and modifications of the updating algorithm for missing observations are suggested." @default.
• W2125804932 created "2016-06-24" @default.
• W2125804932 creator A5072944307 @default.
• W2125804932 date "2008-11-01" @default.
• W2125804932 modified "2023-09-26" @default.
• W2125804932 title "Missing observation analysis for matrix-variate time series data" @default.
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• W2125804932 doi "https://doi.org/10.1016/j.spl.2008.03.033" @default.
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