library(MGMM)
test_that("MVN Complete Data.", {
withr::local_seed(101)
data <- rGMM(n = 1e3, d = 2, k = 1, miss = 0)
fit <- FitMVN(data)
expect_equal(mean(fit), c(0, 0), tolerance = 0.1, ignore_attr = TRUE)
expect_equal(vcov(fit), diag(2), tolerance = 0.1, ignore_attr = TRUE)
})
# -----------------------------------------------------------------------------
test_that("MVN Incomplete Data.", {
withr::local_seed(101)
data <- rGMM(n = 1e3, d = 2, k = 1, miss = 0.2)
fit <- FitMVN(data, report = FALSE)
expect_equal(mean(fit), c(0, 0), tolerance = 0.1, ignore_attr = TRUE)
expect_equal(vcov(fit), diag(2), tolerance = 0.15, ignore_attr = TRUE)
})
# -----------------------------------------------------------------------------
test_that("Rank deficient covariance matrix.", {
skip_on_cran()
withr::local_seed(101)
d <- 10
n <- 9
data <- rGMM(
n = n,
d = d,
k = 1,
means = rep(2, d),
miss = 0.1
)
fit <- expect_error(FitMVN(data, lambda = 1e-1, report = FALSE), NA)
})
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