TY - JOUR
T1 - Fast Computation of Tukey Trimmed Regions and Median in Dimension p > 2
AU - Liu, Xiaohui
AU - Mosler, Karl
AU - Mozharovskyi, Pavlo
N1 - Publisher Copyright:
© 2019, © 2019 American Statistical Association, Institute of Mathematical Statistics, and Interface Foundation of North America.
PY - 2019/7/3
Y1 - 2019/7/3
N2 - Given data in Rp, a Tukey κ-trimmed region is the set of all points that have at least Tukey depth κ w.r.t. the data. As they are visual, affine equivariant and robust, Tukey regions are useful tools in nonparametric multivariate analysis. While these regions are easily defined and interpreted, their practical use in applications has been impeded so far by the lack of efficient computational procedures in dimension p > 2. We construct two novel algorithms to compute a Tukey κ-trimmed region, a naïve one and a more sophisticated one that is much faster than known algorithms. Further, a strict bound on the number of facets of a Tukey region is derived. In a large simulation study the novel fast algorithm is compared with the naïve one, which is slower and by construction exact, yielding in every case the same correct results. Finally, the approach is extended to an algorithm that calculates the innermost Tukey region and its barycenter, the Tukey median. Supplementary materials for this article are available online.
AB - Given data in Rp, a Tukey κ-trimmed region is the set of all points that have at least Tukey depth κ w.r.t. the data. As they are visual, affine equivariant and robust, Tukey regions are useful tools in nonparametric multivariate analysis. While these regions are easily defined and interpreted, their practical use in applications has been impeded so far by the lack of efficient computational procedures in dimension p > 2. We construct two novel algorithms to compute a Tukey κ-trimmed region, a naïve one and a more sophisticated one that is much faster than known algorithms. Further, a strict bound on the number of facets of a Tukey region is derived. In a large simulation study the novel fast algorithm is compared with the naïve one, which is slower and by construction exact, yielding in every case the same correct results. Finally, the approach is extended to an algorithm that calculates the innermost Tukey region and its barycenter, the Tukey median. Supplementary materials for this article are available online.
KW - Computational geometry
KW - Depth contours
KW - Depth regions
KW - Halfspace depth
KW - Location depth
KW - R-package TukeyRegion
KW - Tukey depth
KW - Tukey median
U2 - 10.1080/10618600.2018.1546595
DO - 10.1080/10618600.2018.1546595
M3 - Article
AN - SCOPUS:85062774141
SN - 1061-8600
VL - 28
SP - 682
EP - 697
JO - Journal of Computational and Graphical Statistics
JF - Journal of Computational and Graphical Statistics
IS - 3
ER -