Bayesian inference and impact of parameter prior specification in flexible multilevel nonlinear models in the context of infectious disease modeling
Bayesian flexible multilevel nonlinear models (FMNLMs) are powerful tools to analyze infectious disease data with asymmetric and unbalanced structures, such as varying epidemic stages across countries. However, the robustness of these models can be undermined by poorly designed estimation methods, p...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2025-03-01
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| Series: | Mathematical Biosciences and Engineering |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2025032 |
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