Outliers are those samples which falls above the upper boundary or below the lower boundary where,
the upper boundary equals 1.5 times the IQR above the 75'th percentile and the lower boundary equals 1.5 times the IQR below the 25'th percentile. To support outlier detection in non-symmetrical distributions, the medcouple estimator is used when calculating the upper and lower boundaries.
Medcouple, a robust concept and estimator of skewness. The medcouple is defined as a scaled median difference of the left and right half of the distribution, and hence not based on the third moment as the classical skewness
See here for more details.
Two utilities are included in this package:
- Extracting outliers from a vector
- Remove outliers from a vector
- Extracting outliers from a vector
outliers <- Outliers::Outlier.Orchestration()
output <- 1000 |> rnorm(10,5) |> outliers[['Extract']]()- Remove outliers from a vector
outliers <- Outliers::Outlier.Orchestration()
output <- 1000 |> rnorm(10,5) |> outliers[['Remove']]()note: Github workflows use Github Secrets to set environment variables