I have data that is trying to predict on a given day how much of something we will have.

We have how many things we put into progress, and we want to learn the success failure rate, as well as the general amount per individual. In a sense we are trying to learn

y-estimate = N * failure_rate * individual_estimate

N - number of things

failure_rate - how many will get to the finish line

individual_estimate - what is the average value of these things

I want to learn:

- failure rate as a binomial (aggregating the successes and failures)
- individual estimate by look at each element (removing failures)

I am having trouble understanding if you can learn individual model parameters and aggregate them into one larger model with different aggregations. Thoughts?