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#' Ties function: univariate
#'
#' This function computes the distinct observations and their frequencies in a
#' numeric vector.
#'
#' For internal use.
#'
#' @keywords internal
#' @examples
#'
#' ## The function is currently defined as
#' function(y) {
#' n <- length(y)
#' mat <- outer(y, y, "==")
#' jstar <- led <- rep(FALSE, n)
#' for (j in seq(n)) {
#' if (!led[j]) {
#' jstar[j] <- TRUE
#' if (j == n) {
#' break
#' }
#' ji <- seq(j + 1, n)
#' tt <- mat[ji, j] %in% TRUE
#' led[ji] <- led[ji] | tt
#' }
#' if (all(led[-seq(j)])) {
#' break
#' }
#' }
#' ystar <- y[jstar]
#' nstar <- apply(mat[, jstar], 2, sum)
#' r <- length(nstar)
#' idx <- match(y, ystar)
#' return(list(ystar = ystar, nstar = nstar, r = r, idx = idx))
#' }
comp1 <-
function(y) {
n <- length(y)
mat <- outer(y, y, "==")
jstar <- led <- rep(FALSE, n)
for (j in seq(n)) {
if (!led[j]) {
jstar[j] <- TRUE
if (j == n) {
break
}
ji <- seq(j + 1, n)
tt <- mat[ji, j] %in% TRUE
led[ji] <- led[ji] | tt
}
if (all(led[-seq(j)])) {
break
}
}
ystar <- y[jstar]
nstar <- apply(as.matrix(mat[, jstar]), 2, sum)
r <- length(nstar)
idx <- match(y, ystar)
return(list(ystar = ystar, nstar = nstar, r = r, idx = idx))
}
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