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Likelihood-Free Inference in High-Dimensional Models
Methods that bypass analytical evaluations of the likelihood function have become an indispensable tool for statistical inference in many fields of science. These so-called likelihood-free methods rely on accepting and rejecting simulations based on summary statistics, which limits them to low-dimen...
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| Publicado no: | Genetics |
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| Main Authors: | , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Genetics Society of America
2016
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4896201/ https://ncbi.nlm.nih.gov/pubmed/27052569 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1534/genetics.116.187567 |
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