tests/testthat/test-compute_corrected_mse.R

In KatarzynaReluga/postcAIC: Post-cAIC selection inference under Linear Mixed Models

n = 10
m_i = 5
m_total = 50

clusterID = rep(1:n, m_i)
p = 10
beta = rep(2, p)
u_i = rnorm(n, 0, 2)
u_i_aug = rep(u_i, each = m_i)
X = matrix(rnorm(m_total * p), m_total, p)
y = X%*%beta + u_i_aug + rnorm(m_total, 0, 1)
fit_nerm <- estimate_NERM(X = X, y = y, clusterID = clusterID, X_cluster = NULL)
C_cluster = cbind(X[1:10, ], diag(n))
mse_second = compute_corrected_mse(C_cluster, X, sig_u = fit_nerm$sig_u,
                                  sig_e = fit_nerm$sig_e,
                                  clusterID = clusterID)


test_that("Output is correct", {
  expect_length(mse_second, 2)
  expect_match(class(mse_second), "list")
  expect_length(mse_second$mse, n)
  expect_match(class(mse_second$mse), "numeric")
  expect_length(mse_second$mse_corrected, n)
  expect_match(class(mse_second$mse_corrected), "numeric")
})