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Unbiased Bayesian inference for population Markov jump processes via random truncations
We consider continuous time Markovian processes where populations of individual agents interact stochastically according to kinetic rules. Despite the increasing prominence of such models in fields ranging from biology to smart cities, Bayesian inference for such systems remains challenging, as thes...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer US
2016
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5477715/ https://www.ncbi.nlm.nih.gov/pubmed/28690370 http://dx.doi.org/10.1007/s11222-016-9667-9 |