Overview
The roahd (Robust Analysis of High-dimensional Data) package (Ieva et al. 2019) allows to use a set of statistical tools for the exploration and robustification of univariate and multivariate functional data sets through the use of depth-based statistical methods.
In the implementation of functions, special attention was put to their efficiency, so that they can be profitably used also for the analysis of high-dimensional datasets.
For a full-featured description of the package, please take a look at the roahd vignette.
New feature
We added tools for manipulating and visualizing depthgrams (Aleman-Gomez et al. 2021). This mathematical constructs aim at facilitating the visualization of outliers in high dimensional functional data sets. The depthgram() function computes a number of depthgrams from the functional data set. An S3 specialized method for plot() makes it possible to visualize the depthgrams and proceed with a visual inspection at outliers.