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Infectious disease prediction with kernel conditional density estimation
Creating statistical models that generate accurate predictions of infectious disease incidence is a challenging problem whose solution could benefit public health decision makers. We develop a new approach to this problem using kernel conditional density estimation (KCDE) and copulas. We obtain pred...
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| Veröffentlicht in: | Stat Med |
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| Hauptverfasser: | , , , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
2017
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5771499/ https://ncbi.nlm.nih.gov/pubmed/28905403 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.7488 |
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