I am experimenting with the
CausalImpact package https://google.github.io/CausalImpact/CausalImpact.html (Brodersen et al. 2015) which uses Bayesian structural time-series models.
All of their examples have many time points pre and post intervention.
In my data set, I only have 4 measurements before the intervention, and 20 after the intervention.
Is this a problem for the validity of the model?
I could not find something about how many time points you should have, but for example, the very similar
prophet package says you should have many.
I can provide several covariates, perhaps that helps.