https://github.com/cran/bayestestR
Tip revision: 428249f43a9c6fd0c425b28deb5fee51a9525d69 authored by Dominique Makowski on 18 September 2022, 01:46:03 UTC
version 0.13.0
version 0.13.0
Tip revision: 428249f
test-rope_range.R
test_that("rope_range cor", {
x <- cor.test(ToothGrowth$len, ToothGrowth$dose)
expect_equal(rope_range(x), c(-0.05, 0.05), tolerance = 1e-3)
})
test_that("rope_range gaussian", {
data(mtcars)
mod <- lm(mpg ~ gear + hp, data = mtcars)
expect_equal(rope_range(mod), c(-.1 * sd(mtcars$mpg), .1 * sd(mtcars$mpg)), tolerance = 1e-3)
})
test_that("rope_range log gaussian", {
data(mtcars)
mod <- lm(log(mpg) ~ gear + hp, data = mtcars)
expect_equal(rope_range(mod), c(-0.01, 0.01), tolerance = 1e-3)
})
test_that("rope_range log gaussian 2", {
data(mtcars)
mod <- glm(mpg ~ gear + hp, data = mtcars, family = gaussian("log"))
expect_equal(rope_range(mod), c(-0.01, 0.01), tolerance = 1e-3)
})
test_that("rope_range logistic", {
data(mtcars)
mod <- glm(am ~ gear + hp, data = mtcars, family = binomial())
expect_equal(rope_range(mod), c(-1 * 0.1 * pi / sqrt(3), 0.1 * pi / sqrt(3)), tolerance = 1e-3)
})
.runThisTest <- Sys.getenv("RunAllbayestestRTests") == "yes"
# if (.runThisTest && require("brms", quietly = TRUE)) {
# test_that("rope_range", {
# model <- brm(mpg ~ wt + gear, data = mtcars, iter = 300)
#
# expect_equal(
# rope_range(model),
# c(-0.6026948, 0.6026948),
# tolerance = 0.01
# )
# })
#
# test_that("rope_range (multivariate)", {
# model <- brm(mvbind(mpg, disp) ~ wt + gear, data = mtcars, iter = 300)
#
# expect_equal(
# rope_range(model),
# list(
# mpg = c(-0.602694, 0.602694),
# disp = c(-12.393869, 12.393869)
# ),
# tolerance = 0.01
# )
# })
# }