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InfoVis Is So Much More: A Comment on Gelman and Unwin and an Invitation to Consider the Opportunities
Authors:Robert Kosara
Abstract:We propose new tools for visualizing large amounts of functional data in the form of smooth curves. The proposed tools include functional versions of the bagplot and boxplot, which make use of the first two robust principal component scores, Tukey’s data depth and highest density regions.

By-products of our graphical displays are outlier detection methods for functional data. We compare these new outlier detection methods with existing methods for detecting outliers in functional data, and show that our methods are better able to identify outliers.

An R-package containing computer code and datasets is available in the online supplements.
Keywords:Highest density regions  Kernel density estimation  Outlier detection  Robust principal component analysis  Tukey’s halfspace location depth
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