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Markov chain Monte Carlo without likelihoods
Many stochastic simulation approaches for generating observations from a posterior distribution depend on knowing a likelihood function. However, for many complex probability models, such likelihoods are either impossible or computationally prohibitive to obtain. Here we present a Markov chain Monte...
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| Autors principals: | , , , |
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| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
National Academy of Sciences
2003
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC307566/ https://ncbi.nlm.nih.gov/pubmed/14663152 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.0306899100 |
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