Forecasting daily COVID-19 cases with gradient boosted regression trees and other methods: evidence from U.S. cities

• Autors principals: Anindya Sen (Autor), Nathaniel T. Stevens (Autor), N. Ken Tran (Autor), Rishav R. Agarwal (Autor), Qihuang Zhang (Autor), Joel A. Dubin (Autor)
• Format: Llibre
• Publicat: Frontiers Media S.A., 2023-12-01T00:00:00Z.
• Matèries: article
• Accés en línia: Connect to this object online.

IntroductionThere is a vast literature on the performance of different short-term forecasting models for country specific COVID-19 cases, but much less research with respect to city level cases. This paper employs daily case counts for 25 Metropolitan Statistical Areas (MSAs) in the U.S. to evaluate...