skip_if_not_installed("betareg") data("GasolineYield", package = "betareg") data("FoodExpenditure", package = "betareg") m1 <- betareg::betareg(yield ~ batch + temp, data = GasolineYield) m2 <- betareg::betareg(I(food / income) ~ income + persons, data = FoodExpenditure) test_that("model_info", { expect_true(model_info(m1)$is_beta) expect_false(model_info(m1)$is_linear) }) test_that("find_predictors", { expect_identical(find_predictors(m1), list(conditional = c("batch", "temp"))) expect_identical(find_predictors(m1, flatten = TRUE), c("batch", "temp")) expect_null(find_predictors(m1, effects = "random")) }) test_that("find_response", { expect_identical(find_response(m1), "yield") expect_identical(find_response(m2), "I(food/income)") expect_identical(find_response(m2, combine = FALSE), c("food", "income")) }) test_that("get_response", { expect_equal(get_response(m1), GasolineYield$yield) expect_equal(get_response(m2), FoodExpenditure[, c("food", "income")]) }) test_that("get_varcov", { expect_equal(get_varcov(m1, component = "all"), vcov(m1), tolerance = 1e-3) expect_equal(get_varcov(m1), vcov(m1)[-12, -12], tolerance = 1e-3) }) test_that("link_inverse", { expect_identical(link_inverse(m1)(0.2), plogis(0.2)) }) test_that("get_data", { expect_equal(nrow(get_data(m1)), 32) expect_equal(colnames(get_data(m1)), c("yield", "batch", "temp")) expect_equal(nrow(get_data(m2)), 38) expect_equal( colnames(get_data(m2)), c("food", "income", "persons") ) }) test_that("find_formula", { expect_length(find_formula(m1), 1) expect_equal( find_formula(m1), list(conditional = as.formula("yield ~ batch + temp")), ignore_attr = TRUE ) expect_equal( find_formula(m2), list(conditional = as.formula("I(food/income) ~ income + persons")), ignore_attr = TRUE ) }) test_that("find_variables", { expect_equal( find_variables(m1), list( response = "yield", conditional = c("batch", "temp") ) ) expect_equal( find_variables(m1, flatten = TRUE), c("yield", "batch", "temp") ) expect_equal( find_variables(m2, flatten = TRUE), c("food", "income", "persons") ) }) test_that("n_obs", { expect_equal(n_obs(m1), 32) }) test_that("is_multivariate", { expect_false(is_multivariate(m1)) }) test_that("linkfun", { expect_false(is.null(link_function(m1))) }) test_that("find_parameters", { expect_equal( find_parameters(m1), list( conditional = c( "(Intercept)", "batch1", "batch2", "batch3", "batch4", "batch5", "batch6", "batch7", "batch8", "batch9", "temp" ), precision = "(phi)" ) ) expect_equal(nrow(get_parameters(m1)), 12) expect_equal( get_parameters(m1)$Parameter, c( "(Intercept)", "batch1", "batch2", "batch3", "batch4", "batch5", "batch6", "batch7", "batch8", "batch9", "temp", "(phi)" ) ) }) test_that("find_terms", { expect_equal( find_terms(m2), list( response = "I(food/income)", conditional = c("income", "persons") ) ) }) test_that("find_statistic", { expect_identical(find_statistic(m1), "z-statistic") expect_identical(find_statistic(m2), "z-statistic") }) test_that("get_modelmatrix", { mm <- get_modelmatrix(m1) expect_true(is.matrix(mm)) expect_equal(dim(mm), c(32, 11)) mm <- get_modelmatrix(m1, data = head(GasolineYield)) expect_true(is.matrix(mm)) expect_equal(dim(mm), c(6, 11)) }) test_that("get_predicted", { p <- suppressWarnings(get_predicted(m1)) expect_s3_class(p, "get_predicted") expect_equal(length(p), 32) p <- suppressWarnings(get_predicted(m1, data = head(GasolineYield))) expect_s3_class(p, "get_predicted") expect_equal(length(p), 6) # delta method does not work, so we omit SE and issue warning expect_warning(get_predicted(m2, predict = "expectation")) expect_warning(get_predicted(m2, predict = "link"), NA) p1 <- suppressWarnings(get_predicted(m2, predict = "expectation", ci = 0.95)) p2 <- get_predicted(m2, predict = "link", ci = 0.95) p1 <- data.frame(p1) p2 <- data.frame(p2) expect_true(!"SE" %in% colnames(p1)) expect_true("SE" %in% colnames(p2)) })