Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States

The U.S. COVID-19 Forecast Hub aggregates forecasts of the short-term burden of COVID-19 in the United States from many contributing teams. We study methods for building an ensemble that combines forecasts from these teams. These experiments have informed the ensemble methods used by the Hub. To be...

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Detalles Bibliográficos
Autores principales: Ray, Evan L., Brooks, Logan C., Bien, Jacob, Biggerstaff, Matthew, Bosse, Nikos I., Bracher, Johannes, Cramer, Estee Y., Funk, Sebastian, Gerding, Aaron, Johansson, Michael A., Rumack, Aaron, Wang, Yijin, Zorn, Martha, Tibshirani, Ryan J., Reich, Nicholas G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier B.V. on behalf of International Institute of Forecasters. 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9247236/
https://www.ncbi.nlm.nih.gov/pubmed/35791416
http://dx.doi.org/10.1016/j.ijforecast.2022.06.005

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9247236/
https://www.ncbi.nlm.nih.gov/pubmed/35791416
http://dx.doi.org/10.1016/j.ijforecast.2022.06.005

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