tests/testthat/test-model_sizes.R

In rmsBMA: Reduced Model Space Bayesian Model Averaging

test_that("model_sizes returns three ggplot objects (dilution = 0)", {
  skip_if_not_installed("ggplot2")
  skip_if_not_installed("tidyr")
  skip_if_not_installed("ggpubr")

  set.seed(1)

  n <- 12
  x1 <- rnorm(n)
  x2 <- rnorm(n)
  y  <- 1 + 0.6*x1 - 0.2*x2 + rnorm(n, sd = 0.4)

  data <- cbind(y = y, x1 = x1, x2 = x2)

  ms <- model_space(data, M = 2, g = "None", HC = FALSE)   # K=2 => MS=4
  b  <- bma(ms, EMS = 1, dilution = 0, Narrative = 0, round = 12)

  expect_silent({
    plots <- model_sizes(b)

    expect_type(plots, "list")
    expect_equal(length(plots), 3)

    expect_s3_class(plots[[1]], "ggplot")
    expect_s3_class(plots[[2]], "ggplot")
    expect_s3_class(plots[[3]], "ggplot")

    # Light label sanity (stable and meaningful)
    expect_equal(plots[[1]]$labels$x, "Model size (number of regressors)")
    expect_equal(plots[[1]]$labels$y, "Prior, Posterior")
    expect_equal(plots[[2]]$labels$x, "Model size (number of regressors)")
    expect_equal(plots[[2]]$labels$y, "Prior, Posterior")
  })
})

test_that("model_sizes returns three ggplot objects (dilution = 1)", {
  skip_if_not_installed("ggplot2")
  skip_if_not_installed("tidyr")
  skip_if_not_installed("ggpubr")

  set.seed(2)

  n <- 12
  x1 <- rnorm(n)
  x2 <- rnorm(n)
  y  <- 1 + 0.2*x1 + rnorm(n, sd = 0.5)

  data <- cbind(y = y, x1 = x1, x2 = x2)

  ms <- model_space(data, M = 2, g = "None", HC = FALSE)
  b  <- bma(ms, EMS = 1, dilution = 1, dil.Par = 0.5, Narrative = 0, round = 12)

  expect_silent({
    plots <- model_sizes(b)

    expect_type(plots, "list")
    expect_equal(length(plots), 3)

    expect_s3_class(plots[[1]], "ggplot")
    expect_s3_class(plots[[2]], "ggplot")
    expect_s3_class(plots[[3]], "ggplot")

    # Same stable label checks
    expect_equal(plots[[1]]$labels$x, "Model size (number of regressors)")
    expect_equal(plots[[1]]$labels$y, "Prior, Posterior")
    expect_equal(plots[[2]]$labels$x, "Model size (number of regressors)")
    expect_equal(plots[[2]]$labels$y, "Prior, Posterior")
  })
})