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Inference for discretely observed stochastic kinetic networks with applications to epidemic modeling
We present a new method for Bayesian Markov Chain Monte Carlo–based inference in certain types of stochastic models, suitable for modeling noisy epidemic data. We apply the so-called uniformization representation of a Markov process, in order to efficiently generate appropriate conditional distribut...
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| Main Authors: | , |
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| Format: | Artigo |
| Language: | Inglês |
| Published: |
Oxford University Press
2012
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3276272/ https://ncbi.nlm.nih.gov/pubmed/21835814 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/biostatistics/kxr019 |
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