package setup

0. If you don’t have ‘development tools’ (compilers etc.) installed, do that first. You can try the instructions here or here.
1. Install rstan (install.packages("rstan")).
2. Install cmdstanr.

From https://mc-stan.org/cmdstanr/articles/cmdstanr.html:

while (!require("cmdstanr")) {
    install.packages("cmdstanr", 
            repos = c("https://mc-stan.org/r-packages/", 
                  getOption("repos", "https://cloud.r-project.org")))
}
check_cmdstan_toolchain(fix = TRUE, quiet = TRUE)

3. Install other packages

orig_pkgs <- c(
    ## core
    "lme4", "brms",
    ## model evaluation/testing/plotting
    "broom.mixed",  "tidybayes", "bayesplot", "posterior", "bayestestR",
    ## general purpose manipulation/plotting
    "dplyr", "purrr", "cowplot",
    "ggrastr",  ## rasterize layers with lots of stuff
    "see"  ## for okabe-ito scales
)
ip <- installed.packages()
pkgs <- setdiff(orig_pkgs, rownames(ip))
if (length(pkgs)>0) install.packages(pkgs)

---

These examples were generated using the following package versions:

sapply(sort(c(orig_pkgs, "cmdstanr", "rstan")), \(x) as.character(packageVersion(x)))

##   bayesplot  bayestestR        brms broom.mixed    cmdstanr     cowplot 
##    "1.10.0"    "0.13.1"    "2.20.4"   "0.2.9.5"     "0.7.1"     "1.1.3" 
##       dplyr     ggrastr        lme4   posterior       purrr       rstan 
##     "1.1.2"     "1.0.2"  "1.1.35.1"     "1.5.0"     "1.0.1"    "2.32.6" 
##         see   tidybayes 
##     "0.8.2"     "3.0.6"

cmdstanr::cmdstan_version()

## [1] "2.33.1"