# Ms.GSI paper example data set

# install Ms.GSI through Github
devtools::install_github("boppingshoe/Ms.GSI", build_vignettes = TRUE)
library(Ms.GSI)

# load data files to environment
dat_names <- c("mix_ayk_205", # mixture
               "base_ayk10", # broad-scale baseline
               "base_yukon380_5grps", # regional baseline
               "ayk_pops60_5grps", # broad-scale population
               "yukon_pops43_4grps") # regional populations
for(i in dat_names) load(paste0(i, ".rda"))
rm(dat_names, i)

msgsi_dat <- prep_msgsi_data(mix_ayk, base_ayk10, base_yukon380_5grps, ayk_pops60_5grps, yukon_pops43_4grps, sub_group = 2:5)

msgsi_out <- msgsi_mdl(msgsi_dat, nreps = 5000, nburn = 2500, thin = 1, nchains = 4)

# summarize group proportions
msgsi_out$summ_comb

tr_plot(msgsi_out$trace_comb) # plot posterior trace

# look up document for individual assignment
?Ms.GSI::indiv_assign

indiv_assign(msgsi_out, msgsi_dat)