A two-component Bayesian model, combining an asymmetric-Gaussian ILI forecast with a discrepancy term and a hospitalization regression, placed second among 21 non-ensemble models in the 2023-24 CDC FluSight challenge.
This is an example of an autoregressive model with exogenous variables where the autoregressive lag is one (ARX(1)) [Raftery et al., 2010, Ljung, 1987]
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Forecasting Influenza Hospitalizations Using a Bayesian Hierarchical Nonlinear Model with Discrepancy
A two-component Bayesian model, combining an asymmetric-Gaussian ILI forecast with a discrepancy term and a hospitalization regression, placed second among 21 non-ensemble models in the 2023-24 CDC FluSight challenge.