hampel_outlier.RdRetrieves the bottom and top boundaries to flag outliers or extreme values, according to the Hampel method. This technique takes into account the median and MAD value, which is a is a robust measure of the variability of a univariate sample of quantitative data (Wikipedia). Similar to standard deviation but less sensitve to outliers. This function is used in 'prep_outliers' function. All `NA`s values are automatically excluded. More information at: https://livebook.datascienceheroes.com/data-preparation.html#how_to_deal_with_outliers_in_r.
hampel_outlier(input, k_mad_value = 3)
| input | Numeric variable vector |
|---|---|
| k_mad_value | 'K' multiplier for the median absolute deviation. The higher the value, the more outliers will be detected. Default value=3 (it's an standad) |
A two-item vector, the first value represents the bottom threshold, while the second one is the top threshold
if (FALSE) { hampel_outlier(heart_disease$age) }