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ENH: Functions for summarizing multiple model fitting results.
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Although there is a question about how to handle multiple summaries with summary_col.
Python: Do not show dummies in statsmodels summary
However, I thought more featured functions to achieve easy functions of handling with multiple fitting results were needed, and I tried to implement simple one with just horizontal concatenations, and one version which lets a mosaic variable to control layout of outputs.
See the link below for practical usage. https://github.com/toshiakiasakura/statsmodels/blob/summary_multi/examples/notebooks/summary_multi_usage.ipynb
If there is a further suggestion, improvement or need to open a issue, please tell me.
Hello @toshiakiasakura! Thanks for updating this PR. We checked the lines you've touched for PEP 8 issues, and found:
There are currently no PEP 8 issues detected in this Pull Request. Cheers! :beers:
Comment last updated at 2022-06-29 11:01:43 UTC
@toshiakiasakura
Thanks for the PR
I might not get around looking at this very soon. I'm setting up a new notebook with dev environment and I will soon go on vacation and travelling. (I'm trying to get Window 11 to behave like my old Windows 7 or 8)
Currently, I'm working on your code reviews, and I happened to remember to ask you how to add attributes... Whan I run the following code, I obtain the result as below.
import statsmodels.api as sm
import statsmodels.formula.api as smf
df = sm.datasets.anes96.load_pandas().data
res1 = smf.glm(formula="vote ~ logpopul" ,data=df, family = sm.families.Binomial()).fit()
res2 = sm.add_params_summary(res1)
print(res2.params_summary.to_string())
coef std err t P>|t| [0.025 0.975] str
Intercept -0.073026 0.083061 -0.879178 3.793048e-01 -0.235823 0.089772 -0.073 (-0.236, 0.090)
logpopul -0.110967 0.021216 -5.230224 1.693043e-07 -0.152550 -0.069383 -0.111 (-0.153, -0.069)
However, when I run dir(res2), .params_summary does not appear.
I want to let .params_summary can be found from dir method.
I can not figure out which should be modified.
I'm sorry to rush you, but what's going on for this pull request?
Are there some problems, or should I improve my pull request?
I just came back from my vacation and travelling. I will try to look at it during the next few days.
API decisions are difficult and I need to try this out to see how it works.
These look like very useful functions, thanks for this PR!