Author: Norden E Huang; Fangli Qiao; Ka-Kit Tung
Title: A data-driven tool for tracking and predicting the course of COVID-19 epidemic as it evolves Document date: 2020_3_30
ID: mxen3n0k_177
Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.28.20046177 doi: medRxiv preprint differentiation of empirical data). The positive and negative outliers one day before 968 and after 12 Feb are caused by the spike up and then down, with little effect on the 969 fitted linear trend (but increases its variance and therefore uncertainty). Moreover, 970 the straight line extends without app.....
Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.03.28.20046177 doi: medRxiv preprint differentiation of empirical data). The positive and negative outliers one day before 968 and after 12 Feb are caused by the spike up and then down, with little effect on the 969 fitted linear trend (but increases its variance and therefore uncertainty). Moreover, 970 the straight line extends without appreciable change in slope beyond the peak of 971 N(t), suggesting that the distribution of the newly infected number is approximately 972
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