Retrieves 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:

hampel_outlier(input, k_mad_value = 3)



Numeric variable vector


'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) }