data("gar_data")
test_params = list()
test_params$horizon_list = c(4,8)
test_params$quantile_vec = c(0.05,0.5,0.9)
test_obj = run_GaR_analysis(
partitions_list = list(dom_macro = c("gdp"),
fin_cycle = c("credit")),
vars_df = gar_data,
target_var_name = "gdp",
horizon_list = test_params$horizon_list,
quantile_vec = test_params$quantile_vec)
test_that(
desc = "calculate_skew_and_iqr returns proper object",
expect_equal(
object = test_obj %>%
calculate_skew_and_iqr(quantile_values = c(0.05, 0.5, 0.9)) %>%
colnames(),
expected = c("date", "horizon", "skew", "iqr")
)
)
test_that(
desc = "calculate_skew_and_iqr stops on error if quantiles are missing",
expect_error(
object = test_obj %>%
calculate_skew_and_iqr(),
regexp = "the following quantile(s) are missing in the model object: 0.25,0.75",
fixed = TRUE
)
)
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