Nothing
# The pure-R graphical lasso underpins fit_graphical_var(); test it against its own
# stationarity (KKT) conditions and validate its input guards.
test_that(".glasso_fit satisfies the KKT optimality conditions", {
set.seed(1)
X <- matrix(stats::rnorm(200 * 5), ncol = 5)
S <- stats::cov(X)
rho <- 0.1
fit <- idiographic:::.glasso_fit(S, rho)
v <- idiographic:::.glasso_kkt_violation(fit$wi, S, rho)
expect_lt(v, 1e-6)
})
test_that(".glasso_fit rejects malformed input", {
expect_error(idiographic:::.glasso_fit(matrix(1:6, 2, 3), 0.1), "square")
bad <- matrix(c(1, NA, NA, 1), 2)
expect_error(idiographic:::.glasso_fit(bad, 0.1), "non-finite")
asym <- matrix(c(1, 0.5, 0.2, 1), 2)
expect_error(idiographic:::.glasso_fit(asym, 0.1), "symmetric")
S <- diag(2)
expect_error(idiographic:::.glasso_fit(S, -1), "non-negative")
})
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