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A Generalized, Likelihood-Free Method for Posterior Estimation
Recent advancements in Bayesian modeling have allowed for likelihood-free posterior estimation. Such estimation techniques are crucial to the understanding of simulation-based models, whose likelihood functions may be difficult or even impossible to derive. However, current approaches are limited by...
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| Main Authors: | , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2014
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4143986/ https://ncbi.nlm.nih.gov/pubmed/24258272 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3758/s13423-013-0530-0 |
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