tests/testthat/test-fitted-values.R

# Test fitted_values()

fv_nms <- c(".fitted", ".se", ".lower_ci", ".upper_ci")

test_that("fitted_values() works for a GAM", {
  expect_silent(fv <- fitted_values(m_gam))

  expect_named(fv, expected = c(".row", "x0", "x1", "x2", "x3", fv_nms))

  expect_s3_class(fv, c("tbl_df", "tbl", "data.frame"))

  expect_identical(nrow(su_eg1), nrow(fv))
})

test_that("fitted_values() scale='response' works for a GAM", {
  expect_silent(fv <- fitted_values(m_gam, scale = "response"))
  expect_silent(fv2 <- fitted_values(m_gam, scale = "linear predictor"))

  expect_named(fv, expected = c(".row", "x0", "x1", "x2", "x3", fv_nms))

  expect_s3_class(fv, c("tbl_df", "tbl", "data.frame"))

  expect_identical(nrow(su_eg1), nrow(fv))

  expect_identical(fv, fv2)
})

test_that("fitted_values() scale='link' works for a GAM", {
  expect_silent(fv <- fitted_values(m_gam, scale = "link"))

  expect_named(fv, expected = c(".row", "x0", "x1", "x2", "x3", fv_nms))

  expect_s3_class(fv, c("tbl_df", "tbl", "data.frame"))

  expect_identical(nrow(su_eg1), nrow(fv))
})

test_that("fitted_values() works for a GAM", {
  new_df <- data_sim("eg1", n = 100, dist = "normal", scale = 2, seed = 1)
  expect_silent(fv <- fitted_values(m_gam, data = new_df))

  expect_named(fv, expected = c(".row", names(new_df), fv_nms))

  expect_s3_class(fv, c("tbl_df", "tbl", "data.frame"))

  expect_identical(nrow(new_df), nrow(fv))
})


test_that("fitted_values() works for an ocat GAM", {
  expect_silent(fv <- fitted_values(m_ocat))

  expect_named(fv, expected = c(
    ".row", "x0", "x1", "x2", "x3", ".category",
    fv_nms
  ))
  expect_s3_class(fv, c("tbl_df", "tbl", "data.frame"))
  expect_identical(nrow(su_eg1_ocat) * 4L, nrow(fv))

  new_df <- data_sim("eg1", n = 50, dist = "ocat", seed = 1)
  expect_silent(fv <- fitted_values(m_ocat, data = new_df))
  expect_named(fv, expected = c(".row", names(new_df), ".category", fv_nms))
  expect_s3_class(fv, c("tbl_df", "tbl", "data.frame"))
  expect_identical(nrow(new_df) * 4L, nrow(fv))

  # link scale
  expect_silent(fv <- fitted_values(m_ocat, scale = "link"))
  expect_named(fv, expected = c(".row", "x0", "x1", "x2", "x3", fv_nms))
  expect_s3_class(fv, c("tbl_df", "tbl", "data.frame"))
  expect_identical(nrow(su_eg1_ocat), nrow(fv))

  new_df <- data_sim("eg1", n = 50, dist = "ocat", seed = 1)
  expect_silent(fv <- fitted_values(m_ocat, data = new_df, scale = "link"))
  expect_named(fv, expected = c(".row", names(new_df), fv_nms))
  expect_s3_class(fv, c("tbl_df", "tbl", "data.frame"))
  expect_identical(nrow(new_df), nrow(fv))
})

test_that("fitted values works for a univariate scam model", {
  expect_silent(fv <- fitted_values(m_scam))
  expect_named(fv, expected = c(".row", "x1", "x2", fv_nms))
})

test_that("fitted values works for a ziplss model", {
  expect_silent(fv <- fitted_values(m_ziplss))
  expect_named(fv, expected = c(".row", ".parameter", fv_nms))
})

test_that("fitted values works for a gaulss model", {
  expect_silent(fv <- fitted_values(m_gaulss))
  expect_named(fv, expected = c(".row", ".parameter", fv_nms))
})

test_that("fitted values works for a twlss model", {
  expect_silent(fv <- fitted_values(m_twlss))
  expect_named(fv, expected = c(".row", ".parameter", fv_nms))
  expect_identical(
    pull(fv, ".parameter") |> unique(),
    c("location", "power", "scale")
  )
})

test_that("fitted values works for a gamm model", {
  expect_silent(fv <- fitted_values(m_gamm))
  expect_named(fv, expected = c(".row", "x0", "x1", "x2", "x3", fv_nms))
})
gavinsimpson/gratia documentation built on May 4, 2024, 8:13 a.m.