roahd 1.4.3

An R package for the robust analysis of high-dimensional data.

functional data

Department of Mathematics Jean Leray, UMR CNRS 6629


January 31, 2022


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.


Aleman-Gomez, Yasser, Ana Arribas-Gil, Manuel Desco, Antonio Elias-Fernandez, and Juan Romo. 2021. “Visualizing Outliers in High Dimensional Functional Data for Task fMRI Data Exploration.” arXiv Preprint arXiv:2103.08874.
Ieva, Francesca, Anna Maria Paganoni, Juan Romo, and Nicholas Tarabelloni. 2019. roahd Package: Robust Analysis of High Dimensional Data.” The R Journal 11 (2): 291–307.