Identify Outliers Using Boxplot Heuristic

Detects outliers in a numeric vector using the boxplot heuristic (default, outside 1.5 times the IQR from the 1st and 3rd quartiles). Handles missing values (NA) automatically.

Usage

outlier(x, coef = 1.5, rpt = FALSE)

Arguments

x: Numeric vector for which outliers are to be detected.
coef: Numeric value for boxplot heuristic coefficient (default is 1.5). Higher values result in fewer points being classified as outliers.
rpt: Logical. If FALSE (default), returns a logical vector indicating which elements of x are outliers. If TRUE, returns the calculated lower and upper limits for outlier detection, identified by x < rpt[1] | x > rpt[2].

Value

If rpt = FALSE, returns a logical vector indicating outliers. If rpt = TRUE, returns a numeric vector of length 2 giving lower and upper limits for outlier detection

Examples

set.seed(1)
vals <- c(rnorm(100), 10, -10)
outlier(vals)
#>   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#>  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#>  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#>  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#>  [49] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#>  [61] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#>  [73] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#>  [85] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
#>  [97] FALSE FALSE FALSE FALSE  TRUE  TRUE
outlier(vals, rpt = TRUE)
#>     lower     upper 
#> -2.358805  2.527535