# Running a subnational level single-country model with custom data

## Load your library

    library(mcmsupply)
    library(dplyr)
    set.seed(1209)

## Try to use unsuitable data. The `get_data` function throws an error indicating that the Method column is missing from the custom user-supplied data.

    cleaned_data <- get_data(national=FALSE, local=TRUE,
                             surveydata_filepath = "~/Documents/R/mcmsupply/inst/data-raw/my_custom_subnational_data_bad.xlsx",
                             mycountry="Ethiopia")

    ## Error in check_format(subnat_FPsource_format, subnat_FPsource_data): DATA FORMAT ERROR: Column Method is missing or incorrectly named.

## Load the suitable data

    cleaned_data <- get_data(national=FALSE, local=TRUE,
                             surveydata_filepath = "~/Documents/R/mcmsupply/inst/data-raw/my_custom_subnational_data_good.xlsx",
                             mycountry="Ethiopia")

## Get the JAGS model inputs and the cleaned data

    pkg_data <- get_modelinputs(startyear=1990, endyear=2025.5,
                                nsegments=12, raw_data = cleaned_data)

## Run JAGS model and get posterior point estimates with uncertainty

    mod <- run_jags_model(jagsdata = pkg_data, jagsparams = NULL,
                          n_iter = 40000, n_burnin = 10000, n_thin = 15)

## Plot posterior point estimates with uncertainty

    plots <- plot_estimates(jagsdata = pkg_data, model_output = mod)

## Pull out estimates that you are particularly interested in

    estimates_2018 <- pull_estimates(model_output = mod, country = 'Ethiopia', year=2018)

    head(estimates_2018)