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make sure all possible bernoulli models are detected (#816)
* make sure all possible bernoulli models are detected * tests * fix test issues * suppress warnings * typo
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,28 +1,85 @@ | ||
| skip_if_not_installed("BayesFactor") | ||
| 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) | ||
| }) | ||
|
|
||
| model <- BayesFactor::proportionBF(15, 25, p = 0.5) | ||
| mi <- insight::model_info(model) | ||
| 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) | ||
| }) | ||
|
|
||
| model <- prop.test(15, 25, p = 0.5) | ||
| mi <- insight::model_info(model) | ||
| test_that("model_info-BF-proptest", { | ||
| 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$is_correlation) | ||
| }) | ||
|
|
||
| skip_if_not_installed("tweedie") | ||
|
|
||
| d <- data.frame(x = 1:20, y = rgamma(20, shape = 5)) | ||
| # Fit a poisson generalized linear model with identity link | ||
| model <- glm(y ~ x, data = d, family = statmod::tweedie(var.power = 1, link.power = 1)) | ||
| mi <- insight::model_info(model) | ||
| test_that("model_info-tweedie", { | ||
| skip_if_not_installed("tweedie") | ||
| skip_if_not_installed("statmod") | ||
| d <- data.frame(x = 1:20, y = rgamma(20, shape = 5)) | ||
| # Fit a poisson generalized linear model with identity link | ||
| model <- glm(y ~ x, data = d, family = statmod::tweedie(var.power = 1, link.power = 1)) | ||
| mi <- model_info(model) | ||
| expect_true(mi$is_tweedie) | ||
| expect_false(mi$is_poisson) | ||
| expect_equal(mi$family, "Tweedie") | ||
| expect_identical(mi$family, "Tweedie") | ||
| }) |
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