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Bayes factor Tutorial #1444
Bayes factor Tutorial #1444
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Codecov ReportAttention: Patch coverage is
❗ Your organization needs to install the Codecov GitHub app to enable full functionality. Additional details and impacted files@@ Coverage Diff @@
## develop #1444 +/- ##
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+ Coverage 83.34% 83.46% +0.12%
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Files 159 160 +1
Lines 13356 13473 +117
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+ Hits 11131 11245 +114
- Misses 2225 2228 +3 ☔ View full report in Codecov by Sentry. |
Just some typos.
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From my side this looks good now and is a nice enhancement. Thanks.
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Thanks for the addition.
Co-authored-by: Paul Jonas Jost <[email protected]>
Co-authored-by: Paul Jonas Jost <[email protected]>
Co-authored-by: Paul Jonas Jost <[email protected]>
…s_factor_tutorial
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Looks good! Thanks for the implementations!
@dilpath what do you think? |
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I agree with Domagoj, the notebook is great, and thanks for adding so many methods for computing the marginal likelihood. Looks great!
doc/example/bayes_factors.ipynb
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" \n", | ||
" if 'true_params' in m.keys():\n", | ||
" visualize.parameters(\n", | ||
" results=m['results'], reference={'x': m[\"true_params\"], 'fval': m['problem'].objective(m[\"true_params\"])})\n", |
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This line and many others are cut-off by the width of the rendered notebook.
@PaulJonasJost do we have some ruff
to auto-format notebook code to e.g. 80 characters per line?
…s_factor_tutorial
Adding some new methods to compute marginal likelihoods and Bayes Factors. This inclues:
I also created a notebook explaining how to use these (and other methods already available in pypesto).