# NOT RUN {
# Loading data - population and sample data
data("eusilcA_pop")
data("eusilcA_smp")
# Generate emdi object with two additional indicators; here via function ebp()
emdi_model <- ebp(fixed = eqIncome ~ gender + eqsize + cash +
self_empl + unempl_ben + age_ben + surv_ben + sick_ben + dis_ben + rent +
fam_allow + house_allow + cap_inv + tax_adj, pop_data = eusilcA_pop,
pop_domains = "district", smp_data = eusilcA_smp, smp_domains = "district",
threshold = function(y){0.6 * median(y)}, L = 50, MSE = TRUE, B = 50,
custom_indicator = list( my_max = function(y, threshold){max(y)},
my_min = function(y, threshold){min(y)}), na.rm = TRUE, cpus = 1)
# Example 1: Export estimates for all indicators and uncertainty measures and
# diagnostics to Excel
write.excel(emdi_model, file = "excel_output_all.xlsx", indicator = "all",
MSE = TRUE, CV = TRUE)
# Example 2: Single Excel sheets for point, MSE and CV estimates
write.excel(emdi_model, file = "excel_output_all_split.xlsx", indicator = "all",
MSE = TRUE, CV = TRUE, split = TRUE)
# Example 3: Same as example 1 but for an ODS output
write.ods(emdi_model, file = "ods_output_all.ods", indicator = "all",
MSE = TRUE, CV = TRUE)
# }
# NOT RUN {
# }
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