Check covariance matrix

These functions check whether the input fulfills the properties of a covariance matrix.

Usage

check_covariance_matrix(x, dim = NULL, tolerance = sqrt(.Machine$double.eps))

assert_covariance_matrix(
  x,
  dim = NULL,
  tolerance = sqrt(.Machine$double.eps),
  .var.name = checkmate::vname(x),
  add = NULL
)

test_covariance_matrix(x, dim = NULL, tolerance = sqrt(.Machine$double.eps))

Arguments

x

[any]
Object to check.

dim

[integer(1)]
The matrix dimension.

tolerance

[numeric(1)]
A non-negative tolerance value.

.var.name

[character(1)]
Name of the checked object to print in assertions. Defaults to the heuristic implemented in vname.

add

[AssertCollection]
Collection to store assertion messages. See AssertCollection.

Value

Same as documented in check_matrix.

See also

Other matrix helpers: check_correlation_matrix(), check_transition_probability_matrix(), cov_to_chol(), diff_cov(), insert_matrix_column(), matrix_diagonal_indices(), matrix_indices(), sample_correlation_matrix(), sample_covariance_matrix(), sample_transition_probability_matrix(), stationary_distribution()

Examples

M <- matrix(c(1, 2, 3, 2, 1, 2, 3, 2, 1), nrow = 3)
check_covariance_matrix(M)
#> [1] "Must have positive eigenvalues only"
test_covariance_matrix(M)
#> [1] FALSE
if (FALSE) { # \dontrun{
assert_covariance_matrix(M)
} # }