tests/testthat/test-plot.R

In rifreg: Estimate Recentered Influence Function Regression

test_that("Generic plot method does not throw an error", {
  data <- men8385[1:300, ]
  weights <- men8385$weights[1:300]

  rifreg_object <- rifreg(
    formula = log(wage) ~ union + age,
    data = data,
    statistic = "quantiles",
    custom_rif_function = NULL,
    probs = seq(0.1, 0.9, 0.1),
    weights = weights,
    bootstrap = FALSE,
    bootstrap_iterations = 0,
    cores = 1
  )

  expect_error(plot(rifreg_object), NA)
})


test_that("Generic plot method generates a plot", {
  data <- men8385[1:300, ]
  weights <- men8385$weights[1:300]

  rifreg_object <- rifreg(
    formula = log(wage) ~ union + age,
    data = data,
    statistic = "quantiles",
    custom_rif_function = NULL,
    probs = seq(0.1, 0.9, 0.1),
    weights = weights,
    bootstrap = FALSE,
    bootstrap_iterations = 100,
    cores = 1
  )

  rifreg_plot <- plot(rifreg_object)
  expect_true(is_ggplot(rifreg_plot))
})

test_that("Generic plot method generates a plot with SE", {
  data <- men8385[1:300, ]
  weights <- men8385$weights[1:300]

  rifreg_object <- rifreg(
    formula = log(wage) ~ union + age,
    data = data,
    statistic = "quantiles",
    custom_rif_function = NULL,
    probs = seq(0.1, 0.9, 0.1),
    weights = weights,
    bootstrap = TRUE,
    bootstrap_iterations = 100,
    cores = 1
  )

  rifreg_plot <- plot(rifreg_object)
  expect_true(is_ggplot(rifreg_plot))
})


test_that("Generic plot method generates a plot with different alpha", {
  data <- men8385[1:300, ]
  weights <- men8385$weights[1:300]

  rifreg_object <- rifreg(
    formula = log(wage) ~ union + age,
    data = data,
    statistic = "quantiles",
    custom_rif_function = NULL,
    probs = seq(0.1, 0.9, 0.1),
    weights = weights,
    bootstrap = TRUE,
    bootstrap_iterations = 100,
    cores = 1
  )

  rifreg_plot <- plot(rifreg_object, alpha = 0.1)
  expect_true(is_ggplot(rifreg_plot))
})


test_that("Generic plot method generates a plot with specific variables", {
  data <- men8385[1:300, ]
  weights <- men8385$weights[1:300]

  rifreg_object <- rifreg(
    formula = log(wage) ~ union + age,
    data = data,
    statistic = "quantiles",
    custom_rif_function = NULL,
    probs = seq(0.1, 0.9, 0.1),
    weights = weights,
    bootstrap = TRUE,
    bootstrap_iterations = 100,
    cores = 1
  )

  rifreg_plot <- plot(rifreg_object, varselect = c("age", "unionyes"))
  expect_true(is_ggplot(rifreg_plot))
})

test_that("Generic plot method generates a plot for single quantile", {
  rifreg_object <- rifreg(
    formula = log(wage) ~ union + age,
    data = men8385[1:300, ],
    statistic = "quantiles",
    custom_rif_function = NULL,
    probs = 0.5,
    weights = weights,
    bootstrap = FALSE
  )

  rifreg_plot <- plot(rifreg_object, varselect = c("age", "unionyes"))
  expect_true(is_ggplot(rifreg_plot))
})

test_that("Generic plot method generates a plot for single quantile & bootstrap se", {
  rifreg_object <- rifreg(
    formula = log(wage) ~ union + age,
    data = men8385[1:300, ],
    statistic = "quantiles",
    custom_rif_function = NULL,
    probs = 0.5,
    weights = weights,
    bootstrap = TRUE,
    bootstrap_iterations = 100,
    cores = 1
  )

  rifreg_plot <- plot(rifreg_object, varselect = c("age", "unionyes"))
  expect_true(is_ggplot(rifreg_plot))
})

test_that("Generic plot method generates a plot for RIF of variance", {
  rifreg_object <- rifreg(
    formula = log(wage) ~ union + age,
    data = men8385[1:300, ],
    statistic = "variance",
    custom_rif_function = NULL,
    weights = weights,
    bootstrap = FALSE
  )

  rifreg_plot <- plot(rifreg_object, varselect = c("age", "unionyes"))
  expect_true(is_ggplot(rifreg_plot))
})

test_that("Generic plot method generates a plot for RIF of Gini", {
  rifreg_object <- rifreg(
    formula = log(wage) ~ union + age,
    data = men8385[1:300, ],
    statistic = "gini",
    custom_rif_function = NULL,
    weights = weights,
    bootstrap = FALSE
  )

  rifreg_plot <- plot(rifreg_object, varselect = c("age", "unionyes"))
  expect_true(is_ggplot(rifreg_plot))
})

test_that("Generic plot method generates a plot for RIF of interquantile range", {
  rifreg_object <- rifreg(
    formula = log(wage) ~ union + age,
    data = men8385[1:300, ],
    statistic = "interquantile_range",
    custom_rif_function = NULL,
    probs = c(0.1, 0.9),
    weights = weights,
    bootstrap = FALSE
  )

  rifreg_plot <- plot(rifreg_object, varselect = c("age", "unionyes"))
  expect_true(is_ggplot(rifreg_plot))
})

test_that("Generic plot method generates a plot for RIF of interquantile ratio", {
  rifreg_object <- rifreg(
    formula = log(wage) ~ union + age,
    data = men8385[1:300, ],
    statistic = "interquantile_ratio",
    custom_rif_function = NULL,
    probs = c(0.1, 0.9),
    weights = weights,
    bootstrap = FALSE
  )

  rifreg_plot <- plot(rifreg_object, varselect = c("age", "unionyes"))
  expect_true(is_ggplot(rifreg_plot))
})