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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...
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| Wydane w: | Wellcome Open Res |
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| Główni autorzy: | , , , , |
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
F1000 Research Limited
2019
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| Hasła przedmiotowe: | |
| Dostęp online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7041362/ https://ncbi.nlm.nih.gov/pubmed/32133422 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.12688/wellcomeopenres.15583.1 |
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