Hi Stan-dev,

I’d like to expose model Hessians to R through Rstan with something like `grad_log_prob`

. I have been told by Mike B that the Stan team doesn’t want to do this in a full release because the autodiff Hessians aren’t ready for all models, so I’m happy to hack it up myself in a custom branch. But I think I need some additional guidance.

Looking at the rstan source, it appears that `stan_fit.hpp`

is the first step in exposing C++ functions to R. So I would like to write my own version of

`SEXP grad_log_prob(SEXP upar, SEXP jacobian_adjust_transform)`

However, in the Stan model C++ code, `stan::model::log_prob_grad`

appears to have a different structure than `stan::model::hessian`

In particular, I’m not quite sure how to pass the arguments (`par_r`

and `par_i`

in the log_prob_grad function) into the Hessian. The unit test appears to use a `stan::io::dump`

object:

Upon seeing this, I thought maybe I had better just ask for help. :P Can you someone give me a hand figuring this out?