# numeric -------------------------------
test_that("hdi", {
skip_if_offline()
skip_if_not_or_load_if_installed("rstanarm")
skip_if_not_or_load_if_installed("brms")
skip_if_not_or_load_if_installed("httr")
skip_if_not_or_load_if_installed("BayesFactor")
expect_equal(hdi(distribution_normal(1000), ci = 0.90)$CI_low[1], -1.64, tolerance = 0.02)
expect_equal(nrow(hdi(distribution_normal(1000), ci = c(0.80, 0.90, 0.95))), 3, tolerance = 0.01)
expect_equal(hdi(distribution_normal(1000), ci = 1)$CI_low[1], -3.29, tolerance = 0.02)
expect_identical(nchar(capture.output(print(hdi(distribution_normal(1000))))), 22L)
expect_length(capture.output(print(hdi(distribution_normal(1000), ci = c(0.80, 0.90)))), 5)
expect_message(hdi(c(2, 3, NA)))
expect_warning(hdi(c(2, 3)))
expect_message(hdi(distribution_normal(1000), ci = 0.0000001))
expect_warning(hdi(distribution_normal(1000), ci = 950))
expect_message(hdi(c(0, 0, 0)))
})
# stanreg ---------------------------
test_that("ci", {
skip_if_offline()
skip_if_not_or_load_if_installed("rstanarm")
skip_if_not_or_load_if_installed("brms")
skip_if_not_or_load_if_installed("httr")
skip_if_not_or_load_if_installed("BayesFactor")
m <- insight::download_model("stanreg_merMod_5")
p <- insight::get_parameters(m, effects = "all")
expect_equal(
hdi(m, ci = c(0.5, 0.8), effects = "all")$CI_low,
hdi(p, ci = c(0.5, 0.8))$CI_low,
tolerance = 1e-3
)
})
# brms ---------------------------
test_that("rope", {
skip_if_offline()
skip_if_not_or_load_if_installed("rstanarm")
skip_if_not_or_load_if_installed("brms")
skip_if_not_or_load_if_installed("httr")
skip_if_not_or_load_if_installed("BayesFactor")
m <- insight::download_model("brms_zi_3")
p <- insight::get_parameters(m, effects = "all", component = "all")
expect_equal(
hdi(m, ci = c(0.5, 0.8), effects = "all", component = "all")$CI_low,
hdi(p, ci = c(0.5, 0.8))$CI_low,
tolerance = 1e-3
)
})
# BayesFactor ---------------------------
test_that("ci - BayesFactor", {
skip_if_offline()
skip_if_not_or_load_if_installed("rstanarm")
skip_if_not_or_load_if_installed("brms")
skip_if_not_or_load_if_installed("httr")
skip_if_not_or_load_if_installed("BayesFactor")
mod_bf <- proportionBF(y = 15, N = 25, p = 0.5)
p_bf <- insight::get_parameters(mod_bf)
expect_equal(
hdi(mod_bf, ci = c(0.5, 0.8), effects = "all", component = "all")$CI_low,
hdi(p_bf, ci = c(0.5, 0.8))$CI_low,
tolerance = 0.1
)
})
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.