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Hello @xijianlim ! Thanks for reporting this one! There are a few small nuances that could lead to some difference in response curves vs contribution calculation. Although the difference that...

Hello @xijianlim ! Thanks for your response. There are a couple reasons why those two are designed differently. Mainly the response curves are a forward looking and the other approach...

Hello @satomi999 ! Yes that can happen with certain data and priors. Replacing when you ads are turned off by zeros is fine and our model should be able to...

For `media_prior` you can just pass the values to the `media_prior` param in the `fit` method. For all other priors you can read [the documentation on custom priors](https://lightweight-mmm.readthedocs.io/en/latest/custom_priors.html). For `hill-adstock`...

I have confirmed that the hill adstock functions do not produce `nans` in the presence of zeros so it has to be a tough shape for the model to handle....

@satomi999 thanks for that! Will take a look. In the meantime, can you confirm if your data are impressions, clicks or spend? Could you also mention how are you passing/calculating...

How is `train_s_sums.values` calculated?

Makes sense, just wanted to double check we weren't missing something there. Let me try the mock data you sent and get back to you on this one.

@virithavanama Thanks for requesting this! CSV might not be the format we would return it directly but either an array or DataFrame could be, which is easily converted to CSV....

Hello @chsheth ! Looks like a problem with the arviz library. What version of arviz are you currently using and what python version?