R/Outliers.R

In LeeKennedy/dts.quality: Internal collection of useful little scripts

#' A routine for identifying outliers in a vector of data based on IQR robust statistics.
#' @param x a data set.
#' @param b output boxplot of the four sweeps to remove outliers.  Default is FALSE.
#' @keywords outliers, MU
#' @export
#'

outliers <- function (x, b = FALSE) {
xx <- sapply(x, as.numeric)

#xx <- sort(xx)

remove_outliers <- function(x, na.rm = TRUE, ...) {
  qnt <- quantile(x, probs=c(.25, .75), na.rm = na.rm, ...)
  H <- 1.5 * IQR(x, na.rm = na.rm)
  y <- x
  y[x < (qnt[1] - H)] <- NA
  y[x > (qnt[2] + H)] <- NA
  y
}

yy <- remove_outliers(xx)
ww <- remove_outliers(yy)
zz <- remove_outliers(ww)

diff.out <- data.frame(xx, yy, ww, zz)

if(b == TRUE){
boxplot(diff.out)
}

return(zz)
}