
Bayesian inference and forecast of Covid-19 in Germany by a Max-Planck-Institute - freemint
https://github.com/Priesemann-Group/covid19_inference_forecast/blob/master/README.md
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vital303
I am puzzled by the paper of this groups [1]. The only evidence they present
for "change points in the COVID spreading rate" is slightly better fit of the
number of daily reported cases. In this repository for "Scenario assuming
three change points with a weekly modulation of reported cases" they use 16
parameters to fit a smooth line (wavy pattern is because of lower case reports
around the weekend). An elephant needs 8 [2]!. I also asked for clarification
on stats.stackexchange [3].

[1]
[http://dx.doi.org/10.1126/science.abb9789](http://dx.doi.org/10.1126/science.abb9789)

[2] [http://dx.doi.org/10.1119/1.3254017](http://dx.doi.org/10.1119/1.3254017)

[3]
[https://stats.stackexchange.com/q/467920/286008](https://stats.stackexchange.com/q/467920/286008)

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freemint
This repo is maintained the Max-Planck-Institut für Dynamik und
Selbstorganisation (dynamics and self-organization). The preprint is available
here: [https://arxiv.org/abs/2004.01105](https://arxiv.org/abs/2004.01105)

~~~
freemint
An interview with the leader of this group is available here:
[https://youtube.com/watch?v=nI2_AFzE_ek](https://youtube.com/watch?v=nI2_AFzE_ek)

