if (requiet("mlogit") && requiet("mclogit")) {
data("Fishing")
Fish <-
mlogit.data(Fishing,
varying = c(2:9),
shape = "wide",
choice = "mode"
)
m1 <- mlogit(mode ~ price + catch, data = Fish)
m2 <- mlogit(mode ~ price + catch | income, data = Fish)
test_that("model_info", {
expect_false(model_info(m1)$is_ordinal)
expect_false(model_info(m2)$is_ordinal)
expect_true(model_info(m1)$is_multinomial)
expect_true(model_info(m2)$is_multinomial)
expect_false(model_info(m1)$is_linear)
})
test_that("find_predictors", {
expect_identical(find_predictors(m1), list(conditional = c("price", "catch")))
expect_identical(find_predictors(m1, flatten = TRUE), c("price", "catch"))
expect_null(find_predictors(m1, effects = "random"))
expect_identical(find_predictors(m2), list(conditional = c("price", "catch", "income")))
expect_identical(
find_predictors(m2, flatten = TRUE),
c("price", "catch", "income")
)
expect_null(find_predictors(m2, effects = "random"))
})
test_that("find_response", {
expect_identical(find_response(m1), "mode")
expect_identical(find_response(m2), "mode")
})
if (getRversion() >= "3.6.0") {
test_that("get_response", {
expect_equal(get_response(m1), as.vector(Fish$mode))
})
test_that("get_data", {
expect_equal(nrow(get_data(m1, verbose = FALSE)), 4728)
expect_equal(nrow(get_data(m2, verbose = FALSE)), 4728)
if (packageVersion("mlogit") <= "1.0-3.1") {
expect_equal(
colnames(get_data(m1, verbose = FALSE)),
c("mode", "price", "catch", "probabilities", "linpred")
)
expect_equal(
colnames(get_data(m2, verbose = FALSE)),
c(
"mode",
"price",
"catch",
"income",
"probabilities",
"linpred"
)
)
} else {
expect_equal(
colnames(get_data(m1, verbose = FALSE)),
c("mode", "price", "catch", "idx", "probabilities", "linpred")
)
expect_equal(
colnames(get_data(m2, verbose = FALSE)),
c(
"mode",
"price",
"catch",
"income",
"idx",
"probabilities",
"linpred"
)
)
}
})
}
test_that("link_inverse", {
expect_equal(link_inverse(m1)(0.2), plogis(0.2), tolerance = 1e-5)
expect_equal(link_inverse(m2)(0.2), plogis(0.2), tolerance = 1e-5)
})
test_that("find_formula", {
expect_length(find_formula(m1), 1)
expect_length(find_formula(m2), 1)
})
test_that("find_terms", {
expect_equal(find_terms(m1), list(
response = "mode",
conditional = c("price", "catch")
))
expect_equal(find_terms(m1, flatten = TRUE), c("mode", "price", "catch"))
expect_equal(find_terms(m2), list(
response = "mode",
conditional = c("price", "catch", "income")
))
expect_equal(
find_terms(m2, flatten = TRUE),
c("mode", "price", "catch", "income")
)
})
test_that("n_obs", {
expect_equal(n_obs(m1), 4728)
expect_equal(n_obs(m2), 4728)
})
test_that("linkfun", {
expect_false(is.null(link_function(m1)))
expect_false(is.null(link_function(m2)))
})
test_that("find_statistic", {
expect_identical(find_statistic(m1), "z-statistic")
expect_identical(find_statistic(m2), "z-statistic")
})
}
test_that("mblogit and mclogit is not linear", {
requiet("mclogit")
if (packageVersion("mclogit") >= "0.9.1") {
data(Transport)
mod <- mblogit(factor(gear) ~ mpg + hp, data = mtcars, trace = FALSE)
expect_false(model_info(mod)$is_linear)
expect_true(model_info(mod)$is_logit)
expect_true(is_model(mod))
expect_true(is_model_supported(mod))
mod <- mclogit(resp | suburb ~ distance + cost, data = Transport, trace = FALSE)
expect_false(model_info(mod)$is_linear)
expect_true(model_info(mod)$is_logit)
expect_true(is_model(mod))
expect_true(is_model_supported(mod))
}
})
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