fdaoutlier

A collection of functions for outlier detection in functional data analysis. Methods implemented include directional outlyingness by Dai and Genton (2019) doi:10.1016/j.csda.2018.03.017, MS-plot by Dai and Genton (2018) doi:10.1080/10618600.2018.1473781, total variation depth and modified shape similarity index by Huang and Sun (2019) doi:10.1080/00401706.2019.1574241, and sequential transformations by Dai et al. (2020) doi:10.1016/j.csda.2020.106960 among others. Additional outlier detection tools and depths for functional data like functional boxplot, (modified) band depth etc., are also available.

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