Currently `ei_iter()` takes a fixed number of importance samples to form final estimates. The file `ei_sim.R` ports over all necessary functions from within the `ei` package and alters them to be parameterized. But when this is implemented we get different results in some instances. To replicate this problem, take this section of the `ei_iter` code: https://github.com/RPVote/eiCompare/blob/a65ce945f85d001607f7a4c07b07ca091aa922a3/R/ei_iter.R#L183-L194 Uncomment lines `191-193` and switch `simulate = FALSE`, then compare `ei_iter` results to `ei_est_gen`. Will see large differences, especially where uncertainty is high. This might be due to differences in the namespaces from which functions with `ei_sim` are drawn. The `ei` package is not explicit about which packages it is pulling different distribution-related functions. I have made best guesses based on the imports listed in the `ei` package `NAMESPACE` file, but these could be wrong, or they could be different versions of the same function.