tests/testthat/test-glm_sb2.R

In umich-biostatistics/AdaptiveBayesianUpdates: Adaptive Bayesian Updates

test_that("glm_sb2_binomial runs", {
  expect_type(glm_sb2(y = 0,
                     x_standardized = data.frame(x1 = 0, x2 = 1),
                     family = "binomial",
                     alpha_prior_mean = 0,
                     alpha_prior_cov = matrix(1),
                     aug_projection = matrix(1),
                     mc_warmup = 50,
                     mc_iter_after_warmup = 50,
                     only_prior = TRUE), "list")
})

test_that("glm_sb2_gaussian runs", {
  expect_type(glm_sb2(y = 0,
                     x_standardized = data.frame(x1 = 0, x2 = 1),
                     family = "gaussian",
                     alpha_prior_mean = 0,
                     alpha_prior_cov = matrix(1),
                     aug_projection = matrix(1),
                     mc_warmup = 50,
                     mc_iter_after_warmup = 50,
                     only_prior = TRUE), "list")
})

test_that("glm_sb2_simple_binomial runs", {
  expect_type(glm_sb2(y = 0,
                     x_standardized = data.frame(x1 = 0, x2 = 1),
                     family = "binomial",
                     alpha_prior_mean = 0,
                     alpha_prior_cov = matrix(1),
                     aug_projection = matrix(1),
                     phi_mean = 1,
                     phi_sd = 0,
                     omega_mean = 0,
                     omega_sd = 0,
                     mc_warmup = 50,
                     mc_iter_after_warmup = 50,
                     only_prior = TRUE), "list")
})

test_that("glm_sb2_simple_gaussian runs", {
  expect_type(glm_sb2(y = 0,
                     x_standardized = data.frame(x1 = 0, x2 = 1),
                     family = "gaussian",
                     alpha_prior_mean = 0,
                     alpha_prior_cov = matrix(1),
                     aug_projection = matrix(1),
                     phi_mean = 1,
                     phi_sd = 0,
                     omega_mean = 0,
                     omega_sd = 0,
                     mc_warmup = 50,
                     mc_iter_after_warmup = 50,
                     only_prior = TRUE), "list")
})