Pennoni, F. (2021). A multivariate statistical approach to predict COVID-19 count data with epidemiological interpretation and uncertainty quantification. Intervento presentato a: Meetings of the European Covid-19 Forecast Hub, Milano.

A multivariate statistical approach to predict COVID-19 count data with epidemiological interpretation and uncertainty quantification

Pennoni, F
2021

slide
autoregressive models, Italian COVID-19 data, Dirichlet-Multinomial parametrization, data augmentation algorithm, weekly forecasts of the number of new cases and deaths
English
Meetings of the European Covid-19 Forecast Hub
2021
2021
https://github.com/epiforecasts/covid19-forecast-hub-europe-website/raw/main/presentations/2021-10-06-UpgUmibUsi-MultiBayes.pdf
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Pennoni, F. (2021). A multivariate statistical approach to predict COVID-19 count data with epidemiological interpretation and uncertainty quantification. Intervento presentato a: Meetings of the European Covid-19 Forecast Hub, Milano.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/330835
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