The focus of this paper is on the open-source R package roahd (RObust Analysis of High dimensional Data), see Tarabelloni et al. (2017). roahd has been developed to gather recently proposed statistical methods that deal with the robust inferential analysis of univariate and multivariate functional data. In particular, efficient methods for outlier detection and related graphical tools, methods to represent and simulate functional data, as well as inferential tools for testing differences and dependency among families of curves will be discussed, and the associated functions of the package will be described in details.
Supplementary materials are available in addition to this article. It can be downloaded at RJ-2019-032.zip
Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".
For attribution, please cite this work as
Ieva, et al., "The R Journal: roahd Package: Robust Analysis of High Dimensional Data", The R Journal, 2019
BibTeX citation
@article{RJ-2019-032,
author = {Ieva, Francesca and Paganoni, Anna Maria and Romo, Juan and Tarabelloni, Nicholas},
title = {The R Journal: roahd Package: Robust Analysis of High Dimensional Data},
journal = {The R Journal},
year = {2019},
note = {https://doi.org/10.32614/RJ-2019-032},
doi = {10.32614/RJ-2019-032},
volume = {11},
issue = {2},
issn = {2073-4859},
pages = {291-307}
}