I think there may be a situation where someone has, say,
- GLM model (p=2 params)
- another parameter (i.e.
delta) to estimate that may be most easily handled with an equation solver.
For the model the easiest thing is to probably fit the model & pass it into geex. But for delta., you may want to use the root solver.
It may be nice in this case to allow for compute_roots = c(FALSE, FALSE, TRUE) so that the (p=2) model parameters are ignored in the solver, but the solver does solve for delta_hat.
This is a future-feature; nothing urgent. Your thoughts?
I think there may be a situation where someone has, say,
delta) to estimate that may be most easily handled with an equation solver.For the model the easiest thing is to probably fit the model & pass it into geex. But for
delta., you may want to use the root solver.It may be nice in this case to allow for
compute_roots = c(FALSE, FALSE, TRUE)so that the (p=2) model parameters are ignored in the solver, but the solver does solve fordelta_hat.This is a future-feature; nothing urgent. Your thoughts?