R/uscore.R

In NADA2: Data Analysis for Censored Environmental Data

#' U-score (individual value)
#'
#' @description Computes the uscore of data (required 2-columns) with one or more detection limits.
#' @param y The column of data values plus detection limits
#' @param ind The column of indicators, where 1 (or `TRUE`) indicates a detection limit in the `y` column, and 0 (or `FALSE`) indicates a detected value in `y`.
#' @param rnk  A `TRUE`/`FALSE` variable on whether to compute the multivariate pattern on the uscores, or the ranks of the uscores.  Default is rnk=`TRUE`, use the ranks. rnk = `FALSE` returns the uscores.
#' @export
#' @return prints the uscore number of observations known to be lower - number of observations known to be higher, for each observation.
#'
#' @examples
#' data(Brumbaugh)
#' uscore(Brumbaugh$Hg,Brumbaugh$HgCen)

uscore <- function(y, ind, rnk=TRUE){
  x <- na.omit(data.frame (y, ind))
  n=length(x$y)
  ylo=(1-as.integer(x$ind))*x$y
  # yadj=y
  yadj=x$y-(sign(x$y-ylo)*0.001*x$y)
  overlap=x$y
  Score=overlap
  for (j in 1:n) {
    for (i in 1:n ){
      overlap[i]=sign(sign(yadj[i]-ylo[j])+sign(ylo[i]-yadj[j]))
    }
    Score[j] = -1*sum(overlap) # -1 so that low values = low scores
  }

  if (rnk) {uscore=rank(Score)} else {uscore = Score}
  return(uscore)
}