tests/testthat/test_filter.R

In knockoff: The Knockoff Filter for Controlled Variable Selection

test_that('knockoff.filter verifies input dimensions', {
  expect_error(knockoff.filter(knockoff:::rnorm_matrix(10, 10), rnorm(10), knockoffs=create.fixed), 'dimensions')
  expect_error(knockoff.filter(knockoff:::rnorm_matrix(20, 10), rnorm(19), knockoffs=create.fixed))
  expect_warning(knockoff.filter(knockoff:::rnorm_matrix(20, 15), rnorm(20), knockoffs=create.fixed), 'dimensions')
})

# test_that('knockoff.filter for fixed design is invariant under permutations of the columns of the design matrix.', {
#   # Problem parameters
#   n = 250          # number of observations
#   p = 100          # number of variables
#   k = 30           # number of variables with nonzero coefficients
#   amplitude = 5    # signal amplitude (for noise level = 1)
#   
#   # Generate the variables from a multivariate normal distribution
#   X = matrix(rnorm(n*p),n)
#   
#   # Generate the response from a linear model
#   nonzero = sample(p, k)
#   beta = amplitude * (1:p %in% nonzero) / sqrt(n)
#   y.sample <- function(X) X %*% beta + rnorm(n)
#   y = y.sample(X)
#   
#   # Select variables
#   set.seed(123)
#   S = knockoff.filter(X, y, knockoffs=create.fixed)$selected
#   
#   # Permute columns
#   idx_perm = sample(p)
#   X_perm = X[,idx_perm]
#   set.seed(123)
#   S_perm = idx_perm[knockoff.filter(X_perm, y, knockoffs=create.fixed)$selected]
#   
#   # Verify consistency
#   expect_true(setequal(S,S_perm))
# })