Benjamin T. Vincent
Benjamin T. Vincent
At the moment the model parameters are estimated on the whole pre-intervention period. What we could do instead is to do parameter estimation up to a certain validation window, and...
At the moment `cp.pymc_experiments.InstrumentalVariable` does not have an implementation of the `summary` method. It would be good to add this, and to add test coverage (e.g. in `test_iv_reg` in `test_integration_pymc_examples.py`)...
As of now, we have "vanilla" synthetic control working with ~~`cp.pymc_experiments.SyntheticControl`~~ `cp.SyntheticControl` as the experiment class, and that is fed the `cp.pymc_models.WeightedSumFitter` as the model. It is the `cp.pymc_models.WeightedSumFitter` which...
## Proposal Typically, interrupted time series (ITS) designs are univariate in that there is a single outcome variable. An existing example in the docs examines the causal impact of the...
On pages 304-307 there is an example using CausalPy in Causal Inference and Discovery in Python by @AlxndrMlk. We should create a new pytest file which tests the API to...
### Issue with current documentation: The current installation instructions https://www.pymc.io/projects/docs/en/stable/installation.html have the recommended install method with conda. ### Idea or request for content: But with the rise in popularity of...
In MMM's we have many parameters. Here, let's focus on parameters associated with the saturation function and weighting. Let's just consider a generic saturation function, the contribution of channel $c$...
This is perhaps a meta-proposal which may be fully addressed by multiple separate PR's. But the core idea is to build out the functionality (and visibility of that) on the...
It would be good to maximise the benefits of writing this. So we could put together a paper at JOSS https://joss.theoj.org/
## Description This PR adds a new docs page which demonstrates ability to do causal inference with MMM's. In particular we showcase an example where we run a campaign with...