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Inferring statistical trends of the COVID19 pandemic from current data. Where probability meets fuzziness
We introduce unprecedented tools to infer approximate evolution features of the COVID19 outbreak when these features are altered by containment measures. In this framework we present: (1) a basic tool to deal with samples that are both truncated and non independently drawn, and (2) a two-phase rando...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Elsevier Inc.
2021
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8188773/ https://www.ncbi.nlm.nih.gov/pubmed/34127869 http://dx.doi.org/10.1016/j.ins.2021.06.011 |