Issues of Computational Efficiency and Model Approximation for Spatial Individual-Level Infectious Disease Models
Individual-level models (ILMs) are models that can use the spatial-temporal nature of disease data to capture the disease dynamics. Parameter estimation is usually done via Markov chain Monte Carlo (MCMC) methods, but correlation between model parameters negatively affects MCMC mixing. Introducing a...
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| Language: | en |
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2011
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| Online Access: | http://hdl.handle.net/10214/3248 |