Nothing
test_that(paste("likelihoods_summary computes correct approximations of",
"standard deviations based on economic_growth_ms"), {
set.seed(23)
data_prepared <- bdsm::economic_growth[,1:7] %>%
feature_standardization(timestamp_col = year, entity_col = country) %>%
feature_standardization(timestamp_col = year, entity_col = country,
time_effects = TRUE, scale = FALSE)
lik_info <- likelihoods_summary(df = data_prepared, dep_var_col = gdp,
timestamp_col = year, entity_col = country,
model_space = economic_growth_ms)
expect_equal(lik_info, economic_growth_liks)
})
test_that(paste("parameters_summary computes correct approximations of",
"BMA parameters of interest based on economic_growth_ms"), {
skip_on_os(c("windows", "linux"))
skip_on_cran()
set.seed(20)
data_prepared <- bdsm::economic_growth[,1:7] %>%
feature_standardization(timestamp_col = year, entity_col = country) %>%
feature_standardization(timestamp_col = year, entity_col = country,
time_effects = TRUE, scale = FALSE)
regressors <- regressor_names(data_prepared, year, country, gdp)
bma_result <- bma_summary(df = data_prepared, dep_var_col = gdp,
timestamp_col = year, entity_col = country,
model_space = economic_growth_ms)
bma_params <- parameters_summary(
regressors = regressors, bet = bma_result$bet, pvarh = bma_result$pvarh,
pvarr = bma_result$pvarr, fy = bma_result$fy,
fyt = bma_result$fyt, ppmsize = bma_result$ppmsize,
cout = bma_result$cout, nts = bma_result$nts, pts = bma_result$pts,
variables_n = bma_result$variables_n
)
expect_equal(bma_params, economic_growth_bma_params)
})
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