Add support for na.rm in 'gesd' method.

R/anomalize.R

@@ -13,6 +13,8 @@
 #' @param verbose A boolean. If `TRUE`, will return a list containing useful information
 #' about the anomalies. If `FALSE`, just returns the data expanded with the anomalies and
 #' the lower (l1) and upper (l2) bounds.
+#' @param na.rm Should NA values be removed when calculating outliers? Only
+#' applicable to `"gesd"` method.
 #'
 #' @return Returns a `tibble` / `tbl_time` object or list depending on the value of `verbose`.
 #'
@@ -88,7 +90,7 @@
 #'
 #' @export
 anomalize <- function(data, target, method = c("iqr", "gesd"),
-                      alpha = 0.05, max_anoms = 0.20, verbose = FALSE) {
+                      alpha = 0.05, max_anoms = 0.20, verbose = FALSE, na.rm = FALSE) {
     UseMethod("anomalize", data)
 }
 
@@ -100,7 +102,7 @@ anomalize.default <- function(data, target, method = c("iqr", "gesd"),
 
 #' @export
 anomalize.tbl_df <- function(data, target, method = c("iqr", "gesd"),
-                      alpha = 0.05, max_anoms = 0.20, verbose = FALSE) {
+                      alpha = 0.05, max_anoms = 0.20, verbose = FALSE, na.rm = FALSE) {
 
     # Checks
     if (missing(target)) stop('Error in anomalize(): argument "target" is missing, with no default', call. = FALSE)
@@ -130,6 +132,7 @@ anomalize.tbl_df <- function(data, target, method = c("iqr", "gesd"),
         outlier_list <- anomalize::gesd(x         = x,
                                         alpha     = alpha,
                                         max_anoms = max_anoms,
+                                        na.rm     = na.rm,
                                         verbose   = TRUE)
 
     } else {

R/anomalize_methods.R

@@ -132,7 +132,7 @@ iqr <- function(x, alpha = 0.05, max_anoms = 0.2, verbose = FALSE) {
 
 #' @export
 #' @rdname anomalize_methods
-gesd <- function(x, alpha = 0.05, max_anoms = 0.2, verbose = FALSE) {
+gesd <- function(x, alpha = 0.05, max_anoms = 0.2, verbose = FALSE, na.rm = FALSE) {
 
   # Variables
   n <- length(x)
@@ -151,12 +151,12 @@ gesd <- function(x, alpha = 0.05, max_anoms = 0.2, verbose = FALSE) {
   for (i in seq_len(r)) {
 
     # Compute test statistic
-    median_new[i] <- median(x_new)
-    mad_new[i] <- mad(x_new)
+    median_new[i] <- median(x_new, na.rm = na.rm)
+    mad_new[i] <- mad(x_new, na.rm = na.rm)
 
-    z <- abs(x_new - median(x_new)) / (mad(x_new) + .Machine$double.eps) # Z-scores
+    z <- abs(x_new - median(x_new, na.rm = na.rm)) / (mad(x_new, na.rm = na.rm) + .Machine$double.eps) # Z-scores
 
-    max_ind <- which(z == max(z), arr.ind = T)[1] # in case of ties, return first one
+    max_ind <- which(z == max(z, na.rm = na.rm), arr.ind = T)[1] # in case of ties, return first one
     R[i] <- z[max_ind] # max Z-score
     outlier_val[i] <- x_new[max_ind] # removed outlier observation values
     outlier_ind[i] <- which(x_new[max_ind] == x, arr.ind = T)[1] # index of removed outlier observation values