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Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.

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Hi, I have tried using different dark mode options for the plots locally, but because of some hard-coded colors they become a bit hard to read. Any chance the hard-coded...

As this relies on the BSTS methodology, is there a way to use tfcausalimpact for forecasting alone, i.e. setting the post-period to values beyond the final timestamp of the available...

Hi, thanks for making this nice package! Small question regarding the p-value from `summary`: From [the doc here](https://github.com/WillianFuks/tfcausalimpact/blob/d6057372603902e20026fd5695e29ad9de0285ca/causalimpact/inferences.py#L393) , it seems the range of p-value is from 0 to 1....

Hi, thank you for great work! wanted to check with you, is "trained_model" removed from the latest version of tfcausalimpact? if so, what is the most current method to extract...

I successfully downloaded TensorFlow and TensorFlow probability on M1 12.0 macOS into a Conda environment. When pip installing ufcausalimpact into the environment I get the following error. Note: I can...

Hi there! I noticed that the repo for `pycausalimpact` (https://github.com/dafiti/causalimpact) has been taken down, then saw that you were one of the key contributors to the package, then saw that...

Hi, thank you for all your effort in this library. We have many datasets for which we need to compute causal impact. Currently, it is too slow to compute it...

Thank you for a very nice package. I'm trying to switch from pycausalImapct recently, and I don't fully understand this module yet, so I'll only provide some ideas today. [Idea]....

Can I use only one observed variable and date, then nothing else?