Relatrice: dott.ssa Mitzi Morris (Columbia University)

Abstract A Stan model infers the model parameters given the data.

The data-generating program reverses the computation:
given parameters, it outputs the data according to the specified distributions.
Often simulated datasets are created by one-off scripts in R or Python.
Writing a data-generating program using Stan allows for more systematic
exploration of the consequences of choice of prior and difficult data regimes.