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Bayesian workflow example #797
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Check out this pull request on See visual diffs & provide feedback on Jupyter Notebooks. Powered by ReviewNB |
Not sure if this belongs in case studies or elsewhere ... |
View / edit / reply to this conversation on ReviewNB twiecki commented on 2025-06-19T14:52:53Z A lot of these have not plot? fonnesbeck commented on 2025-06-19T19:58:54Z I don't understand the question. aloctavodia commented on 2025-06-19T20:06:11Z I think he means that a lot of the plots are not visible... fonnesbeck commented on 2025-06-19T20:11:30Z That's odd. Will ask Oriol about this. Would be a shame if we can't use plotly in the docs. fonnesbeck commented on 2025-06-19T20:48:38Z OK, I've fixed this. Thanks. |
View / edit / reply to this conversation on ReviewNB twiecki commented on 2025-06-19T14:55:49Z Maybe add COVID-19 or infection modeling to the title. |
Either case-study or howto, leaning towards the latter. |
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T18:40:00Z The first two sentences could be "Bayesian modeling is a robust approach to draw conclusions from data. Successful modeling involves an interplay..." |
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T18:40:01Z A slightly different way to write this would be
dist = pz.Gamma() pz.maxent(dist, lower=0.1, upper=20, mass=0.95);
Then, in the next cell
fig = px.histogram(x=dist.rvs(1000), nbins=20, title="Gamma Distribution Samples") fig.show()
and in the model
alpha = dist.to_pymc("alpha")
|
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T18:40:01Z we can use
alpha = pz.maxent(pz.Gamma(), lower=0.1, upper=20, mass=0.95, plot=False).to_pymc("alpha")
instead of
gamma_params = pm.find_constrained_prior( pm.Gamma, lower=0.1, upper=20, init_guess={"alpha": 6, "beta": 1}, mass=0.95 ) alpha = pm.Gamma("alpha", **gamma_params) |
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T18:40:02Z plt.tight_layout() not neccesary given that we are using "arviz-doc" style |
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T18:40:03Z plt.show() not neccesary? |
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T18:40:03Z Just for your information "New ArviZ", has functionality for prior/likelihood sensitivity checks, see https://arviz-devs.github.io/EABM/Chapters/Sensitivity_checks.html No needed to be done now, but maybe in a next round of revision we could use "new arviz" its new prior checks, or new plot like rank plots... |
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T18:40:04Z "sampels" |
I don't understand the question. View entire conversation on ReviewNB |
I think he means that a lot of the plots are not visible... View entire conversation on ReviewNB |
That's odd. Will ask Oriol about this. Would be a shame if we can't use plotly in the docs. View entire conversation on ReviewNB |
OK, I've fixed this. Thanks. View entire conversation on ReviewNB |
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T21:03:15Z This can be removed |
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T21:03:16Z Add ; |
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T21:03:16Z Also add ; |
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T21:03:17Z Add ; |
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T21:03:18Z Add ; |
View / edit / reply to this conversation on ReviewNB aloctavodia commented on 2025-06-19T21:03:18Z Add ; |
Everyone cool with these changes? |
A notebook adapted from course material on how to implement Gelman et al.'s Bayesian workflow, using a COVID-19 dataset.
Helpful links
📚 Documentation preview 📚: https://pymc-examples--797.org.readthedocs.build/en/797/