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#' Negative Eigenvalue Magnitude
#'
#' Negative Eigenvalue Magnitude (NEM) is a measure of distortion for the data
#' whether they are lying in Euclidean manner or not. When the value is exactly 0, it means
#' the data is Euclidean. On the other hand, when NEM is far away from 0, it means not Euclidean.
#' The concept of NEM is closely related to the definiteness of a Gram matrix.
#'
#' @param data an \eqn{(n\times p)} matrix whose rows are observations.
#'
#' @return a nonnegative NEM value.
#'
#' @examples
#' ## use simple example of iris dataset
#' data(iris)
#' mydat = as.matrix(iris[,1:4])
#'
#' ## calculate NEM
#' nem(mydat)
#'
#' @references
#' \insertRef{pekalska_noneuclidean_2006}{maotai}
#'
#' @export
nem <- function(data){
############################################################
# Preprocessing
if (!check_datamat(data)){
stop("* nem : an input 'data' should be a matrix without any missing/infinite values.")
}
xdiss = stats::as.dist(cpp_pdist(data))
############################################################
# Compute and Return
output = (xdiss)
return(output)
}
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