Winsorise a vector — winsorise • COINr

Follows a "standard" Winsorisation approach: points are successively Winsorised in order to bring skew and kurtosis thresholds within specified limits. Specifically, aims to bring absolute skew to below a threshold (default 2.25) and kurtosis below another threshold (default 3.5).

Usage

winsorise(
  x,
  na.rm = FALSE,
  winmax = 5,
  skew_thresh = 2,
  kurt_thresh = 3.5,
  force_win = FALSE
)

Arguments

x: A numeric vector.
na.rm: Set TRUE to remove NA values, otherwise returns NA.
winmax: Maximum number of points to Winsorise. Default 5. Set NULL to have no limit.
skew_thresh: A threshold for absolute skewness (positive). Default 2.25.
kurt_thresh: A threshold for kurtosis. Default 3.5.
force_win: Logical: if TRUE, forces winsorisation up to winmax (regardless of skew/kurt). Default FALSE. Note - this option should be used with care because the direction of Winsorisation is based on the direction of skew. Successively Winsorising can switch the direction of skew and hence the direction of Winsorisation, which may not produce the expected behaviour.

Value

A list containing winsorised data, number of winsorised points, and the individual points that were treated.

Details

Winsorisation here is defined as reassigning the point with the highest/lowest value with the value of the next highest/lowest point. Whether to Winsorise at the high or low end of the scale is decided by the direction of the skewness of x.

This function replaces the now-defunct coin_win() from COINr < v1.0.

Examples

# numbers between 1 and 10
x <- 1:10

# two outliers
x <- c(x, 30, 100)

# winsorise
l_win <- winsorise(x, skew_thresh = 2, kurt_thresh = 3.5)

# see treated vector, number of winsorised points and details
l_win
#> $x
#>  [1]  1  2  3  4  5  6  7  8  9 10 30 30
#> 
#> $nwin
#> [1] 1
#> 
#> $treated
#>  [1] ""      ""      ""      ""      ""      ""      ""      ""      ""     
#> [10] ""      ""      "winhi"
#>