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- W4287257427 abstract "In this paper we propose a novel method to deal with Vector Autoregressive models, when the Normal-Wishart prior is considered. In particular, we depart from the current approach of setting $nu=m+1$ by setting a loss-based prior on $nu$. Doing so, we have been able to exploit any information about $nu$ in the data and achieve better predictive performances than the method currently used in the literature. We show how this works both on simulated and real data sets where, in the latter case, we used data of macroeconometric fashion as well as viral data. In addition, we show the reason why we believe we achieve a better performance by showing that the data appears to suggest a value of $nu$ far from the canonical $m+1$ value." @default.
- W4287257427 created "2022-07-25" @default.
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- W4287257427 date "2021-03-23" @default.
- W4287257427 modified "2023-10-18" @default.
- W4287257427 title "Loss based prior for the degrees of freedom of the Wishart distribution" @default.
- W4287257427 doi "https://doi.org/10.48550/arxiv.2103.12900" @default.
- W4287257427 hasPublicationYear "2021" @default.
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