Neither Bayesian nor frequentist fitting is uniformly better for epidemic forecasts; performance depends on phase and data, though the paper's own results undercut its phase-specific claims.
(2020) Outbreak datasets
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
dataset 1
citation-polarity summary
fields
q-bio.QM 1years
2025 1verdicts
REJECT 1roles
dataset 1polarities
use dataset 1representative citing papers
citing papers explorer
-
Comparative study of Bayesian and Frequentist methods for epidemic forecasting: Insights from simulated and historical data
Neither Bayesian nor frequentist fitting is uniformly better for epidemic forecasts; performance depends on phase and data, though the paper's own results undercut its phase-specific claims.