Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States
Evan L. Ray, Logan C. Brooks, Jacob Bien, Matthew Biggerstaff, Nikos I. Bosse, Johannes Bracher, Estee Y. Cramer, Sebastian Funk, Aaron Gerding, Michael A. Johansson, Aaron Rumack, Yijin Wang, Martha Zorn, Ryan J. Tibshirani, Nicholas G. Reich
| Year of publication: |
2023
|
|---|---|
| Authors: | 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. |
| Published in: |
International journal of forecasting. - Amsterdam [u.a.] : Elsevier, ISSN 0169-2070, ZDB-ID 283943-X. - Vol. 39.2023, 3, p. 1366-1383
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| Subject: | COVID-19 | Ensemble | Epidemiology | Health forecasting | Quantile combination | USA | United States | Coronavirus | Prognoseverfahren | Forecasting model | Epidemie | Epidemic | Sterblichkeit | Mortality | Gesundheit | Health | Prognose | Forecast | Gesundheitspolitik | Health policy |
| Type of publication: | Article |
|---|---|
| Type of publication (narrower categories): | Aufsatz in Zeitschrift ; Article in journal |
| Language: | English |
| Other identifiers: | 10.1016/j.ijforecast.2022.06.005 [DOI] |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014465288