In Regression and Other Stories, chapter 15 section 2, as well as on this page:
There’s an example where three different phi values are used (0.1, 1, 10) to generate fake data to fit with
fit_nb[[k]] <- stan_glm(y ~ x, family=neg_binomial_2(link="log"), data=fake, refresh=0)
After fitting the three fake datasets, the three different reciprocal_dispersion values are basically the same at: 10.7, 10.8, and 10.8. I’m a bit surprised, because I thought the phi values would be recovered by the fits, but obviously not. Is there something in the fitting that is supposed to be able to recover the phi values? I’d like to follow the process of recovering the known inputs to the data generating process, but I don’t know how to do that with the available code. Thanks.