-
Notifications
You must be signed in to change notification settings - Fork 285
Multi MMM does not work with time_varying_intercept_ and custom priors #1575
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Comments
@williambdean Regarding the design, how do you view the integration between |
It might not accept that at the moment. Are we expecting to use the I think the This would allow for the different parameter requirements for the classes to be handled within the class itself. It is more flexible with the cost that it becomes a bit more verbose to pass. Maybe we can explore a different interface that makes use of the mmm = MMM(..., # no hsgp information here)
hsgp = HSGP.parameterize_from_data(...)
mmm.add_intercept(hsgp) Bit of a chicken or egg for both of these solutions since the HSGP requires data ( What are your thoughts? |
I agree with removing the |
Thank you for this great library. I understand that we cannot define a custom prior, but would the default prior be a time varying intercept equal across all geographical regions? |
Uh oh!
There was an error while loading. Please reload this page.
I was trying to run the example notebook from #1521 with
and I get the error at build time
I think the issue is we are not not expecting
HSGPKwargs
anywhere as the default config has'intercept_tvp_config': {'ls_lower': 0.3, 'ls_upper': 2.0},
, which is passed topymc-marketing/pymc_marketing/mmm/multidimensional.py
Lines 1109 to 1113 in 06d1a34
However, we are parsing the
model_config
at the init stage:pymc-marketing/pymc_marketing/mmm/multidimensional.py
Lines 297 to 300 in 06d1a34
The text was updated successfully, but these errors were encountered: