covid19_inference
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Priesemann-Group
Bayesian python toolbox for inference and forecast of the spread of the Coronavirus
Hello, I'm trying to fetch data from JHU using the jhu class in **data_retrival/_JHU.py**. When I use the **state** argument in the methods **get_new** and **get_total_confirmed_deaths_recovered**, I get the error...
changed the number of forecast to 15 and also the prior median lambda to 10 days for contact points. This shows how many days it takes for south Africans to...
In PyMC3, stein variational gradient is already implemented, but it has to be tested how well it works/how biased it is for small number of particles. In addition, the optimal...
For windows users plotting functions do not work with default rcParams. As one can see [here ](https://docs.microsoft.com/en-us/cpp/c-runtime-library/reference/strftime-wcsftime-strftime-l-wcsftime-l?redirectedfrom=MSDN&view=vs-2019) Windows does not support `%-d`. Which we use in our default [rcParameters](https://github.com/Priesemann-Group/covid19_inference/blob/6691da24bcb76549fe9c067b6e17b7ca76d51892/covid19_inference/plot.py#L1098). We...
Possible plots: - For one variable: the name of the regions as y axis, x-axis are CI intervals - For each region, table of histograms, one histogram/pdf per variable, like...
Hello. It is difficult to understand the description of the `delay_cases` function parameters. ```python def delay_cases( new_I_t, pr_median_delay=10, pr_sigma_median_delay=0.2, pr_median_scale_delay=0.3, pr_sigma_scale_delay=None, ... ): ``` Perhaps refactoring is needed here: ```...
In order to parametrize better the hierarchical model, a non-centered parametrical distribution is better when the data is not very informative, see for example: https://docs.pymc.io/notebooks/Diagnosing_biased_Inference_with_Divergences.html or https://pdfs.semanticscholar.org/7b85/fb48a077c679c325433fbe13b87560e12886.pdf I implemented it...
@joaopn What is the status there? Otherwise I think that @semohr has also some code to retrieve the mobility data. I just want to avoid diverging development
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Bayesian python toolbox for inference and forecast of the spread of the Coronavirus