R - Parallelizing multiple model learning (with dplyr and purrr)

Question

This is a follow up to a previous question about learning multiple models.

The use case is that I have multiple observations for each subject, and I want to train a mode

Answer 1

There is the furrr package now, for example something like:

library(dplyr)
library(furrr)
plan(multiprocess)

dt %>% 
    split(dt$subject_id) %>%
    future_map(~fitdist(.$observation, "norm"))