I think you could use something like the following (which is a simpler version that avoids where your data comes from, variable names, model specification, and all that)
dir.create("models")
# This function generates a file path, runs the `brm` function and saves the object
# returned by `brm()` as a .rds file
my_fun = function(prior_sd, prior_mean) {
file_name = paste0("models/model_sd_", prior_sd, "_mean_", prior_mean, ".rds")
brms_object = brm(...) # pass formula, prior, data, options, etc.
saveRDS(brms_object, file_name) # you can control compression too if you want
}
sds = c(0.01, 0.01, 0.01)
means = c(50, -50, 0)
purrr::walk2(sds, means, my_fun)
You have to make sure that the data frame you’re going to use exists in the global environment
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