A hierarchical Bayesian approach for modeling the evolution of the 7-day moving average of the number of deaths by COVID-19

DOI10.1080/02664763.2022.2070136MaRDI QIDQ6164668

Carlos Alberto de Bragança Pereira, Lisandra Sauer, Erlandson F. Saraiva

Publication date: 28 July 2023

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10332210

zbMATH Keywords

Gaussian processpredictionsMCMC algorithmBayesian approachCOVID-19

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Unnamed Item
• Diffusion limits of the random walk Metropolis algorithm in high dimensions
• Weak convergence and optimal scaling of random walk Metropolis algorithms
• Weak convergence of Metropolis algorithms for non-I.I.D. target distributions

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