#' The Correlation Pattern Matrix
#'
#' Creates a correlation pattern matrix.
#'
#' \eqn{
#' \mathbf{M}_{k}
#' \left(
#' c
#' \right)
#' }
#' is the
#' \eqn{
#' k \times k
#' }
#' correlation pattern matrix with
#'
#' \deqn{
#' \left(
#' \mathbf{M}_{k}
#' \left(
#' c
#' \right)
#' \right)_{ij, gh}
#' =
#' \begin{cases}
#' \frac{1}{2}
#' &
#' \text{if}
#' \quad
#' \left( i, j \right) = \left( g, h \right)
#' \text{or}
#' \left( i, j \right) = \left( h, g \right),
#' \quad
#' i \neq j
#' ,
#' g \neq h, \\
#' 0
#' &
#' \text{if}
#' \quad
#' i = j = g = h
#' ,
#' \\
#' 0
#' &
#' \text{otherwise}
#' .
#' \end{cases}
#' }
#'
#' @author Ivan Jacob Agaloos Pesigan
#'
#' @inherit mcap_diag references return
#'
#' @inheritParams dcap
#'
#' @examples
#' mcap_cor(3)
#' @family Symmetric Functions
#' @keywords linearAlgebra symmetric
#' @export
mcap_cor <- function(k) {
.check_pos_scalar_int(k)
.mcap_cor(
ms = .mcap_sym(
.dcap(k)
)
)
}
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