test_that("rstanarm", {
skip_on_cran()
skip_if_offline()
skip_if_not_or_load_if_installed("rstanarm")
skip_if_not_or_load_if_installed("httr")
set.seed(333)
model <- insight::download_model("stanreg_lm_1")
expect_equal(rope_range(model, verbose = FALSE)[1], -0.602, tolerance = 0.1)
model <- insight::download_model("stanreg_meanfield_lm_1")
expect_equal(rope_range(model, verbose = FALSE)[1], -0.602, tolerance = 0.1)
model <- insight::download_model("stanreg_fullrank_lm_1")
expect_equal(rope_range(model, verbose = FALSE)[1], -0.602, tolerance = 0.1)
model <- insight::download_model("stanreg_lmerMod_1")
expect_equal(rope_range(model, verbose = FALSE)[1], -0.097, tolerance = 0.1)
model <- insight::download_model("stanreg_glm_1")
expect_equal(rope_range(model, verbose = FALSE)[1], -0.18, tolerance = 0.1)
model <- insight::download_model("stanreg_merMod_1")
expect_equal(rope_range(model, verbose = FALSE)[1], -0.18, tolerance = 0.1)
model <- insight::download_model("stanreg_gamm4_1")
expect_equal(rope_range(model, verbose = FALSE)[1], -0.043, tolerance = 0.1)
model <- insight::download_model("stanreg_gam_1")
invisible(capture.output(
expect_warning(params <- describe_posterior(model,
centrality = "all",
test = "all", dispersion = TRUE
))
))
expect_equal(c(nrow(params), ncol(params)), c(4, 22))
expect_s3_class(hdi(model), "data.frame")
expect_s3_class(ci(model), "data.frame")
expect_s3_class(rope(model, verbose = FALSE), "data.frame")
expect_true(inherits(equivalence_test(model), "equivalence_test"))
expect_s3_class(map_estimate(model), "data.frame")
expect_s3_class(p_map(model), "data.frame")
expect_s3_class(p_direction(model), "data.frame")
expect_error(equivalence_test(model, range = c(0.1, 0.3, 0.5)))
})
test_that("rstanarm", {
skip_on_cran()
skip_if_offline()
skip_if_not_or_load_if_installed("rstanarm")
skip_if_not_or_load_if_installed("httr")
set.seed(333)
model <- insight::download_model("stanreg_glm_3")
out <- describe_posterior(model, effects = "all", component = "all", centrality = "mean")
s <- summary(model)
expect_identical(colnames(out), c(
"Parameter", "Mean", "CI", "CI_low", "CI_high", "pd", "ROPE_CI",
"ROPE_low", "ROPE_high", "ROPE_Percentage", "Rhat", "ESS"
))
expect_equal(as.vector(s[1:4, 1, drop = TRUE]), out$Mean, tolerance = 1e-3)
expect_equal(as.vector(s[1:4, 8, drop = TRUE]), out$Rhat, tolerance = 1e-1)
})
test_that("rstanarm", {
skip_on_cran()
skip_if_offline()
skip_if_not_or_load_if_installed("rstanarm")
skip_if_not_or_load_if_installed("httr")
set.seed(333)
model <- insight::download_model("stanreg_merMod_3")
out <- describe_posterior(model, effects = "all", component = "all", centrality = "mean")
s <- summary(model)
expect_identical(colnames(out), c(
"Parameter", "Effects", "Mean", "CI", "CI_low", "CI_high",
"pd", "ROPE_CI", "ROPE_low", "ROPE_high", "ROPE_Percentage",
"Rhat", "ESS"
))
expect_equal(as.vector(s[1:8, 1, drop = TRUE]), out$Mean, tolerance = 1e-3)
expect_equal(as.vector(s[1:8, 8, drop = TRUE]), out$Rhat, tolerance = 1e-1)
})
test_that("rstanarm", {
skip_on_cran()
skip_if_offline()
skip_if_not_or_load_if_installed("rstanarm")
skip_if_not_or_load_if_installed("httr")
set.seed(333)
model <- insight::download_model("stanmvreg_1")
out <- describe_posterior(model, effects = "fixed", component = "all", centrality = "mean", test = NULL)
s <- summary(model)
expect_identical(colnames(out), c(
"Parameter", "Response", "Mean", "CI", "CI_low", "CI_high",
"Rhat", "ESS"
))
expect_equal(as.vector(s[c(1:2, 5:7), 1, drop = TRUE]), out$Mean, tolerance = 1e-3)
expect_equal(as.vector(s[c(1:2, 5:7), 10, drop = TRUE]), out$Rhat, tolerance = 1e-1)
})
test_that("rstanarm", {
skip_on_cran()
skip_if_offline()
skip_if_not_or_load_if_installed("rstanarm")
skip_if_not_or_load_if_installed("httr")
set.seed(333)
model <- insight::download_model("stanmvreg_1")
out <- describe_posterior(
model,
effects = "fixed",
component = "all",
centrality = "mean",
test = NULL,
priors = TRUE
)
expect_identical(colnames(out), c(
"Parameter", "Response", "Mean", "CI", "CI_low", "CI_high",
"Rhat", "ESS", "Prior_Distribution", "Prior_Location",
"Prior_Scale"
))
expect_equal(nrow(out), 5)
})
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