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Using model-based proposals for fast parameter inference on discrete state space, continuous-time Markov processes
Bayesian statistics provides a framework for the integration of dynamic models with incomplete data to enable inference of model parameters and unobserved aspects of the system under study. An important class of dynamic models is discrete state space, continuous-time Markov processes (DCTMPs). Simul...
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| Gepubliceerd in: | J R Soc Interface |
|---|---|
| Hoofdauteurs: | , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
The Royal Society
2015
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4590508/ https://ncbi.nlm.nih.gov/pubmed/25994297 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1098/rsif.2015.0225 |
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