Hi, I’m working on a 1-parameter model (trying to start small) which is an ODE model with a 10 dimensional state space. The one parameter moves the trajectories around, and likelihood is calculated according to how well a trajectory matches data which are measured for one of the state dimensions. There are 288 data points to be taken into account for the likelihood. I am running Stan via RStan. I’m sure this is all pretty pedestrian.
What I’m seeing is that Stan gets stuck in the warmup phase. The progress messages say 0%, 1%, 2%, very, very slowly advancing. I can print out the values of the sole parameter and it looks like the model is being evaluated over and over for identical or nearly identical values of the parameter. I have tried varying stepsize, stepsize_jitter, adapt_delta, max_treedepth, and warmup; I haven’t yet stumbled across a combination which is materially different.
What are some ideas for debugging or diagnosing what is going on in the warmup phase? I have printed out the parameter so far, and that shows the values are identical or nearly so, which is interesting. What are some other things I can look at? I gather that very small steps are sometimes associated with strong curvature – how could I go about collecting more information about that?
I can post the entire model, it’s not too big, but I would need to do some work on it to make it self-contained. In the meantime if anyone has any advice about things to look at, I would be very grateful.
All the best,