I’m developing a package for TKTD models (Toxicokinetics/Toxicodynamics). My question is about default parameters (number of iteration, adapt_delta, ODE…), the compromise between robustness and speed.
I have around 15 data set to test my package.
- For instance, with 80% of them, adapt_delta=0.8 work fine, but for other I need adapt_delta=0.95 and for one of them adapt_delta=0.99. If I’m right, ‘rstan’ default is 0.8 and ‘rstanarm’ default is 0.95. I didn’t see big different in speed for my datasets, so I’ll probably go for 0.95, and document the case where 0.99 is required.
- For ODEs parameters, the stuff is more complex. I use tolerance parameters at ‘10e-8’, ‘10e-5’, and ‘1e3’, which work fantastic for most of the data set, but I needed to increase at ‘10e-10’, ‘10e-8’, and ‘1e3’ for 3 of them. And this increases the time to compute. So I don’t want it as default, but understanding the way to change those parameters is more complex for a user I guess.
- Also, _rk45 work great for all my examples, but I’m not sure if a specific dataset could work better with _bds. Here, the speed matters a lot.
I understand that, by definition, there is no good answer. But what are the kind of questions I should ask myself when developing the package? And what kind of message I should present to the user?