For my current situation I am looking to set up hierarchical models to describe the data I have where it is a standard situation of having multiple observations per customer across multiple days where one can easily see that the behavior of each customer is more similar to their own than others and therefore wanting to account for that variance independently of a larger model (I have a more statistics-based background).
However within the provided tools in Dataiku there doesn't seem to be any way to fit these kinds of models? I am aware that I am likely to need to write my own here, but wanting to double-check that I'm not reinventing the wheel here? Are there any Bayesian approaches already written within Dataiku using JAGS or similar?
Any advice or hints appreciated!
ETA: Realizing that a more classical way to approach what I'm wanting is with a mixed model (fixed and random effects) but also not finding anything like that within the tools provided?
