A collection of some tests commonly used for identifying
        outliers.

Provides implementations of some of the most important outlier detection algorithms. 
    Includes a tutorial mode option that shows a description of each algorithm and provides 
    a step-by-step execution explanation of how it identifies outliers from the given data 
    with the specified input parameters. References include the works of Azzedine Boukerche, 
    Lining Zheng, and Omar Alfandi (2020) <doi:10.1145/3381028>, Abir Smiti (2020) 
    <doi:10.1016/j.cosrev.2020.100306>, and Xiaogang Su, Chih-Ling Tsai (2011) 
    <doi:10.1002/widm.19>.

Potential outliers are identified for all combinations of a dataset's variables. O3 plots are described in Unwin(2019) <doi:10.1080/10618600.2019.1575226>. The available methods are HDoutliers() from the package 'HDoutliers', FastPCS() from the package 'FastPCS', mvBACON() from 'robustX', adjOutlyingness() from 'robustbase', DectectDeviatingCells() from 'cellWise', covMcd() from 'robustbase'.

Provides tools for multivariate outlier detection based on
    geometric properties of multivariate data using random directional
    projections. Observation-level outlier scores are computed by jointly
    probing radial magnitude and angular alignment through repeated
    projections onto random directions, with optional robust centering and
    covariance adjustment. In addition to global outlier scoring, the method
    produces dimension-level contribution measures to support interpretation
    of detected anomalies. Visualization utilities are included to summarize
    directional contributions for extreme observations.

Outlier detection method that flags suspicious values within observations,
  constrasting them against the normal values in a user-readable format, potentially
  describing conditions within the data that make a given outlier more rare.
  Full procedure is described in Cortes (2020) <doi:10.48550/arXiv.2001.00636>.
  Loosely based on the 'GritBot' <https://www.rulequest.com/gritbot-info.html> software.