Include tail ESS if possible

[bwiernik]

Currently, we only report the bulk ESS. The tail ESS is useful for diagnosising reliability of the interval quantiles and detecting poor mixing. It's available by default from brms objects and can be computed for all Stan models using posterior::ess_tail() (vs. posterior::ess_bulk()).

[bwiernik]

To use rstanarm objects currently, we can use posterior functions by extracting the $stanfit slot from the object.

[mattansb]

Looking at the posterior code, looks like its:

I.05 <- x <= quantile(x, 0.05)
I.95 <- x <= quantile(x, 0.95)
min(ess(I.05), ess(I.95))

[bwiernik]

The Stan packages seem to all be moving to relying on posterior for these sorts of computations, so a soft dependency for Stan models could be okay.

[bwiernik]

Would be really nice if BayesFactor and INLA would also update to work with the posterior S3 generics...

[mattansb]

Would be really nice if BayesFactor and INLA would also update to work with the posterior S3 generics...

Unlikely... That's what we're here for!

I still cannot wrap my head around the rvar data :/

[bwiernik]

My understanding is that rvar are helpful, but we can also just work with numeric R vectors