STAR_outliers: a python package that separates univariate outliers from non-normal distributions

ABSTRACT: There are not currently any univariate outlier detection algorithms that transform and model arbitrarily shaped distributions to remove univariate outliers. Some algorithms model skew, even fewer model kurtosis, and none of them model bimodality and monotonicity. To overcome these challenges, we have implemented an algorithm for Skew and Tail-heaviness Adjusted Removal of Outliers (STAR_outliers) that robustly removes univariate outliers from distributions with many different shape profiles, including extreme skew, extreme kurtosis, bimodality, and monotonicity. We show that STAR_outliers removes simulated outliers with greater recall and precision than several general algorithms, and it also models the outlier bounds of real data distributions with greater accuracy. Background Reliably re

SUBMITTER: Gregg J 

PROVIDER: S-EPMC10476292 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature