test_that("p_direction", {
set.seed(333)
x <- distribution_normal(10000, 1, 1)
pd <- p_direction(x)
expect_equal(as.numeric(pd), 0.842, tolerance = 0.1)
# converstion into frequentist p-value works
p <- p_direction(x, as_p = TRUE)
expect_equal(as.numeric(p), pd_to_p(pd$pd), tolerance = 0.1)
expect_equal(as.vector(p), pd_to_p(pd$pd), tolerance = 0.1)
# return NA
expect_true(is.na(as.numeric(p_direction(c(x, NA), remove_na = FALSE))))
# works
expect_equal(as.numeric(p_direction(c(x, NA))), 0.8413, tolerance = 0.1)
expect_equal(as.vector(p_direction(c(x, NA))), 0.8413, tolerance = 0.1)
# error if only NA
expect_error(p_direction(c(NA_real_, NA_real_)), regex = "No valid values found")
expect_equal(as.numeric(p_direction(x, method = "kernel")), 0.842, tolerance = 0.1)
expect_s3_class(pd, "p_direction")
expect_s3_class(pd, "data.frame")
expect_identical(dim(pd), c(1L, 2L))
expect_identical(
capture.output(print(pd)),
c(
"Probability of Direction", "", "Parameter | pd", "------------------",
"Posterior | 84.13%"
)
)
df <- data.frame(replicate(4, rnorm(100)))
pd <- p_direction(df)
expect_s3_class(pd, "p_direction")
expect_s3_class(pd, "data.frame")
expect_identical(dim(pd), c(4L, 2L))
})
test_that("p_direction", {
skip_if_offline()
skip_if_not_or_load_if_installed("rstanarm")
skip_if_not_or_load_if_installed("brms")
m <- insight::download_model("stanreg_merMod_5")
p <- insight::get_parameters(m, effects = "all")
expect_equal(
p_direction(m, effects = "all")$pd,
p_direction(p)$pd,
tolerance = 1e-3
)
# converstion into frequentist p-value works
expect_equal(
p_direction(m, effects = "all", as_p = TRUE)$p,
pd_to_p(p_direction(m, effects = "all")$pd),
tolerance = 1e-3
)
expect_equal(
p_direction(m, effects = "all", as_p = TRUE)$p,
as.numeric(p_direction(m, effects = "all", as_p = TRUE)),
tolerance = 1e-3
)
expect_equal(
p_direction(m, effects = "all", as_p = TRUE)$p,
as.vector(p_direction(m, effects = "all", as_p = TRUE)),
tolerance = 1e-3
)
})
test_that("p_direction", {
skip_if_offline()
skip_if_not_or_load_if_installed("rstanarm")
skip_if_not_or_load_if_installed("brms")
m <- insight::download_model("brms_zi_3")
p <- insight::get_parameters(m, effects = "all", component = "all")
expect_equal(
p_direction(m, effects = "all", component = "all")$pd,
p_direction(p)$pd,
tolerance = 1e-3
)
})
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