skip_if_not_installed("MASS") data(housing, package = "MASS") m1 <- MASS::polr(Sat ~ Infl + Type + Cont, data = housing, weights = Freq) test_that("model_info", { expect_true(model_info(m1)$is_ordinal) expect_false(model_info(m1)$is_multinomial) }) test_that("find_predictors", { expect_identical(find_predictors(m1), list(conditional = c("Infl", "Type", "Cont"))) expect_identical( find_predictors(m1, flatten = TRUE), c("Infl", "Type", "Cont") ) expect_null(find_predictors(m1, effects = "random")) }) test_that("find_response", { expect_identical(find_response(m1), "Sat") }) test_that("link_inverse", { expect_equal(link_inverse(m1)(0.2), plogis(0.2), tolerance = 1e-5) }) test_that("get_data", { expect_identical(nrow(get_data(m1)), 72L) expect_named( get_data(m1), c("Sat", "Infl", "Type", "Cont", "Freq") ) }) 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"), df.residual(m1), # model has t-statistic ignore_attr = TRUE ) }) test_that("find_formula", { expect_length(find_formula(m1), 1) expect_equal( find_formula(m1), list(conditional = as.formula("Sat ~ Infl + Type + Cont")), ignore_attr = TRUE ) }) test_that("find_terms", { expect_identical(find_terms(m1), list( response = "Sat", conditional = c("Infl", "Type", "Cont") )) expect_identical( find_terms(m1, flatten = TRUE), c("Sat", "Infl", "Type", "Cont") ) }) test_that("n_obs", { expect_identical(n_obs(m1), 1681L) }) test_that("linkfun", { expect_false(is.null(link_function(m1))) }) test_that("find_parameters", { expect_identical( find_parameters(m1), list( conditional = c( "Intercept: Low|Medium", "Intercept: Medium|High", "InflMedium", "InflHigh", "TypeApartment", "TypeAtrium", "TypeTerrace", "ContHigh" ) ) ) }) test_that("get_parameters", { expect_equal( get_parameters(m1), data.frame( Parameter = c( "Intercept: Low|Medium", "Intercept: Medium|High", "InflMedium", "InflHigh", "TypeApartment", "TypeAtrium", "TypeTerrace", "ContHigh" ), Estimate = c( -0.4961353438375, 0.690708290379271, 0.566393738890106, 1.28881906381232, -0.572350146429611, -0.366186566153346, -1.09101490767244, 0.360284149947385 ), stringsAsFactors = FALSE, row.names = NULL ), tolerance = 1e-5, ignore_attr = TRUE ) }) test_that("find_statistic", { expect_identical(find_statistic(m1), "t-statistic") }) test_that("get_predicted", { p1 <- get_predicted(m1, predict = "expectation") p2 <- get_predicted(m1, predict = "classification") p3 <- get_predicted(m1, predict = NULL, type = "probs") p4 <- get_predicted(m1, predict = NULL, type = "class") expect_s3_class(p1, "get_predicted") expect_s3_class(p2, "get_predicted") expect_s3_class(p3, "get_predicted") expect_s3_class(p4, "get_predicted") expect_identical(p1, p3) expect_identical(p2, p4) expect_s3_class(p1, "data.frame") expect_s3_class(p2, "factor") expect_s3_class(p3, "data.frame") expect_s3_class(p4, "factor") expect_true(all(c("Row", "Response", "Predicted") %in% colnames(p1))) expect_true(all(c("Row", "Response", "Predicted") %in% colnames(p3))) d <- get_datagrid(m1, by = "Type", verbose = FALSE) p1 <- get_predicted(m1, predict = "expectation", data = d, verbose = FALSE) expect_named(p1, c("Row", "Type", "Response", "Predicted")) expect_identical(dim(p1), c(12L, 4L)) })