test_that("glm bernoulli", {
data(mtcars)
model <- glm(vs ~ disp, data = mtcars, family = binomial())
mi <- model_info(model)
expect_true(mi$is_binomial)
expect_true(mi$is_bernoulli)
})
test_that("geeglm bernoulli", {
skip_if_not_installed("geepack")
data(mtcars)
model <- geepack::geeglm(
vs ~ disp,
data = mtcars,
id = cyl,
family = binomial()
)
mi <- model_info(model)
expect_true(mi$is_binomial)
expect_true(mi$is_bernoulli)
})
test_that("bigglm bernoulli", {
skip_if_not_installed("bigglm")
data(mtcars)
model <- biglm::bigglm(
vs ~ disp,
family = binomial(),
data = mtcars
)
mi <- model_info(model)
expect_true(mi$is_binomial)
expect_true(mi$is_bernoulli)
})
test_that("glmmTMB bernoulli", {
skip_if_not_installed("glmmTMB")
data(mtcars)
model <- glmmTMB::glmmTMB(vs ~ disp, data = mtcars, family = binomial())
mi <- model_info(model)
expect_true(mi$is_binomial)
expect_true(mi$is_bernoulli)
model <- glmmTMB::glmmTMB(vs ~ disp + (1 | cyl), data = mtcars, family = binomial())
mi <- model_info(model)
expect_true(mi$is_binomial)
expect_true(mi$is_bernoulli)
})
test_that("glmer bernoulli", {
skip_if_not_installed("lme4")
data(mtcars)
model <- lme4::glmer(vs ~ disp + (1 | cyl), data = mtcars, family = binomial())
mi <- model_info(model)
expect_true(mi$is_binomial)
expect_true(mi$is_bernoulli)
})
test_that("model_info-BF-proptest", {
skip_if_not_installed("BayesFactor")
model <- BayesFactor::proportionBF(15, 25, p = 0.5)
mi <- model_info(model)
expect_true(mi$is_binomial)
expect_false(mi$is_linear)
})
test_that("model_info-proptest", {
model <- prop.test(15, 25, p = 0.5)
mi <- model_info(model)
expect_true(mi$is_binomial)
expect_false(mi$is_linear)
expect_false(mi$is_correlation)
})
test_that("model_info-tweedie", {
skip_if_not_installed("tweedie")
skip_if_not_installed("statmod")
d <- data.frame(x = 1:20, y = rgamma(20, shape = 5))
# Fit a poisson generalized linear model with identity link
model <- glm(y ~ x, data = d, family = statmod::tweedie(var.power = 1, link.power = 1))
mi <- model_info(model)
expect_true(mi$is_tweedie)
expect_false(mi$is_poisson)
expect_identical(mi$family, "Tweedie")
})
test_that("model_info, glm bernoulli", {
set.seed(1)
tot <- rep(10, 100)
suc <- rbinom(100, prob = 0.9, size = tot)
dat <- data.frame(tot, suc)
dat$prop <- suc / tot
mod <- glm(prop ~ 1,
family = binomial,
data = dat,
weights = tot
)
expect_true(model_info(mod)$is_binomial)
expect_false(model_info(mod)$is_bernoulli)
data(mtcars)
mod <- glm(am ~ 1, family = binomial, data = mtcars)
expect_true(model_info(mod)$is_binomial)
expect_true(model_info(mod)$is_bernoulli)
})
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.