skip_if_not_installed("glmmTMB")
data(Salamanders, package = "glmmTMB")
Salamanders$cover <- abs(Salamanders$cover)
dat <<- Salamanders
m1 <- glm(count ~ mined + log(cover) + sample,
family = poisson,
data = dat
)
test_that("model_info", {
expect_true(model_info(m1)$is_poisson)
expect_true(model_info(m1)$is_count)
expect_false(model_info(m1)$is_negbin)
expect_false(model_info(m1)$is_binomial)
expect_false(model_info(m1)$is_linear)
})
test_that("loglik", {
expect_equal(get_loglikelihood(m1), logLik(m1), ignore_attr = TRUE)
})
test_that("get_df", {
expect_equal(get_df(m1), df.residual(m1), ignore_attr = TRUE)
expect_equal(get_df(m1, type = "model"), attr(logLik(m1), "df"), ignore_attr = TRUE)
})
test_that("get_df", {
expect_equal(
get_df(m1, type = "residual"),
df.residual(m1),
ignore_attr = TRUE
)
expect_equal(
get_df(m1, type = "normal"),
Inf,
ignore_attr = TRUE
)
expect_equal(
get_df(m1, type = "wald"),
Inf,
ignore_attr = TRUE
)
})
test_that("find_predictors", {
expect_identical(find_predictors(m1), list(conditional = c("mined", "cover", "sample")))
expect_identical(
find_predictors(m1, flatten = TRUE),
c("mined", "cover", "sample")
)
expect_null(find_predictors(m1, effects = "random"))
})
test_that("find_random", {
expect_null(find_random(m1))
})
test_that("get_random", {
expect_warning(get_random(m1))
})
test_that("find_response", {
expect_identical(find_response(m1), "count")
})
test_that("get_response", {
expect_identical(get_response(m1), Salamanders$count)
})
test_that("get_predictors", {
expect_identical(colnames(get_predictors(m1)), c("mined", "cover", "sample"))
})
test_that("link_inverse", {
expect_equal(link_inverse(m1)(0.2), exp(0.2), tolerance = 1e-5)
})
test_that("linkfun", {
expect_equal(link_function(m1)(0.2), -1.609438, tolerance = 1e-4)
})
test_that("get_data", {
expect_identical(nrow(get_data(m1)), 644L)
expect_identical(
colnames(get_data(m1)),
c("count", "mined", "cover", "sample")
)
})
test_that("get_call", {
expect_true(inherits(get_call(m1), "call")) # nolint
})
test_that("find_formula", {
expect_length(find_formula(m1), 1)
expect_equal(
find_formula(m1),
list(conditional = as.formula("count ~ mined + log(cover) + sample")),
ignore_attr = TRUE
)
})
test_that("find_variables", {
expect_identical(
find_variables(m1),
list(
response = "count",
conditional = c("mined", "cover", "sample")
)
)
expect_identical(
find_variables(m1, flatten = TRUE),
c("count", "mined", "cover", "sample")
)
})
test_that("n_obs", {
expect_identical(n_obs(m1), 644L)
})
test_that("find_parameters", {
expect_identical(
find_parameters(m1),
list(
conditional = c("(Intercept)", "minedno", "log(cover)", "sample")
)
)
expect_identical(nrow(get_parameters(m1)), 4L)
expect_identical(
get_parameters(m1)$Parameter,
c("(Intercept)", "minedno", "log(cover)", "sample")
)
})
test_that("is_multivariate", {
expect_false(is_multivariate(m1))
})
test_that("find_terms", {
expect_identical(
find_terms(m1),
list(
response = "count",
conditional = c("mined", "log(cover)", "sample")
)
)
})
test_that("find_algorithm", {
expect_identical(find_algorithm(m1), list(algorithm = "ML"))
})
test_that("find_statistic", {
expect_identical(find_statistic(m1), "z-statistic")
})
test_that("get_statistic", {
expect_equal(
get_statistic(m1)$Statistic,
c(
-10.7066515607315,
18.1533878215937,
-1.68918157150882,
2.23541768590273
),
tolerance = 1e-4
)
})
test_that("model_info, bernoulli", {
skip_if_not_installed("lme4")
data(cbpp, package = "lme4")
m <- glm(
cbind(incidence, size - incidence) ~ size + period,
family = binomial(),
data = cbpp
)
info <- model_info(m)
expect_true(info$is_binomial)
expect_false(info$is_bernoulli)
expect_true(info$is_logit)
expect_true(info$is_trial)
expect_identical(info$family, "binomial")
data(mtcars)
m <- glm(
am ~ cyl,
family = binomial(),
data = mtcars
)
info <- model_info(m)
expect_true(info$is_binomial)
expect_true(info$is_bernoulli)
expect_true(info$is_logit)
expect_false(info$is_trial)
expect_identical(info$family, "binomial")
})
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