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Loss-based prior for the degrees of freedom of the Wishart distribution

Rossini, Luca, Villa, Cristiano, Prevenas, Sotiris, McCrea, Rachel (2024) Loss-based prior for the degrees of freedom of the Wishart distribution. Econometrics and Statistics, . ISSN 2452-3062. (doi:10.1016/j.ecosta.2024.04.001) (KAR id:105607)

Abstract

Motivated by the proliferation of extensive macroeconomic and health datasets necessitating accurate forecasts, a novel approach is introduced to address Vector Autoregressive (VAR) models. This approach employs the global-local shrinkage-Wishart prior. Unlike conventional VAR models, where degrees of freedom are predetermined to be equivalent to the size of the variable plus one or equal to zero, the proposed method integrates a hyperprior for the degrees of freedom to account for the uncertainty in the parameter values. Specifically, a loss-based prior is derived to leverage information regarding the data-inherent degrees of freedom. The efficacy of the proposed prior is demonstrated in a multivariate setting both for forecasting macroeconomic data, and Dengue infection data.

Item Type: Article
DOI/Identification number: 10.1016/j.ecosta.2024.04.001
Uncontrolled keywords: Forecasting, Global-local Shrinkage Prior, Loss-based prior, Macroeconomic data, Vector Autoregressive models
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science
SWORD Depositor: JISC Publications Router
Depositing User: JISC Publications Router
Date Deposited: 19 Apr 2024 14:01 UTC
Last Modified: 22 Apr 2024 15:37 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/105607 (The current URI for this page, for reference purposes)

University of Kent Author Information

Prevenas, Sotiris.

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