tests/testthat/test-linearAlgebra-kcap.R

In jeksterslab/gammaMatrix: Asymptotic Covariance Matrix of Covariances

## ---- test-linearAlgebra-kcap
x_i <- matrix(
  data = c(
    1.0, 0.5, 0.4,
    0.5, 1.0, 0.6,
    0.4, 0.6, 1.0
  ),
  ncol = 3
)
m_i <- dim(x_i)[1]
answer_i <- c(1.0, 0.5, 0.4, 1.0, 0.6, 1.0)
result_i <- c(kcap(m_i) %*% as.vector(x_i))
testthat::test_that("test-linearAlgebra-kcap 3 by 3", {
  testthat::expect_equal(
    result_i,
    answer_i
  )
})
x_i <- matrix(
  c(1, 2, 2, 3),
  ncol = 2
)
m_i <- dim(x_i)[1]
answer_i <- c(1, 2, 3)
result_i <- c(kcap(m_i) %*% as.vector(x_i))
testthat::test_that("test-linearAlgebra-kcap 2 by 2", {
  testthat::expect_equal(
    result_i,
    answer_i
  )
})
n_i <- 100
k_i <- sample(
  1:10,
  size = 1
)
mu_i <- rep(
  x = 0,
  times = k_i
)
sigmacap_i <- matrix(
  runif(
    n = 1,
    min = 0,
    max = 1
  ),
  nrow = k_i,
  ncol = k_i
)
diag(sigmacap_i) <- 1
x_i <- matrix(
  data = rnorm(
    n = n_i * k_i
  ),
  nrow = n_i,
  ncol = k_i
) %*% (
  chol(sigmacap_i)
) + (
  matrix(
    data = 1,
    nrow = n_i,
    ncol = 1
  ) %*% mu_i
)
x_i <- cov(x_i)
m_i <- dim(x_i)[1]
answer_i <- vech(t(x_i), names = FALSE)
result_i <- c(kcap(m_i) %*% as.vector(x_i))
testthat::test_that("test-linearAlgebra-kcap random cov", {
  testthat::expect_equal(
    result_i,
    answer_i
  )
})
# clean environment
rm(
  x_i,
  m_i,
  answer_i,
  result_i,
  n_i,
  k_i,
  mu_i,
  sigmacap_i
)