bootstrap_runner: Runs the bootstrapping of the models.
In glmmboot: Bootstrap Resampling for Mixed Effects and Plain Models

This function gets passed a function that runs a single bootstrap resample and a number of resamples, and decides how to run them e.g. in parallel etc.

bootstrap_runner(
  bootstrap_function,
  resamples,
  parallelism = c("none", "future", "parallel"),
  num_cores = NULL,
  future_packages = NULL
)

`bootstrap_function`	Function that we wish to run `resamples` times.
`resamples`	How many resamples of your data do you want to do? 9,999 is a reasonable default (see Hesterberg 2015), but start very small to make sure it works on your data properly, and to get a rough timing estimate etc.
`parallelism`	Type of parallelism (if any) to use to run the resamples. Options are: `"none"` The default, sequential `"future"` To use `future.apply` (`future`s) `"parallel"` To use `parallel::mclapply`
`num_cores`	How many cores to use. Defaults to `parallel::detectCores() - 1L` if `parallelism = "parallel"`
`future_packages`	Packages to pass to created futures when using `parallelism = "future"`. This must be supplied if the package used to model the data isn't in base and you're using a plan that doesn't have shared memory, because the model is updated with the S3 generic `update`.