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PYLFIRE: Python implementation of likelihood-free inference by ratio estimation
Likelihood-free inference for simulator-based models is an emerging methodological branch of statistics which has attracted considerable attention in applications across diverse fields such as population genetics, astronomy and economics. Recently, the power of statistical classifiers has been harne...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
F1000 Research Limited
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7041362/ https://www.ncbi.nlm.nih.gov/pubmed/32133422 http://dx.doi.org/10.12688/wellcomeopenres.15583.1 |