This article proposes an informative exploratory tool, the functional boxplot, for visualizing
functional data, as well as its generalization, the enhanced functional boxplot. Based on the …

Statistical depth functions are being formulated ad hoc with increasing popularity in
nonparametric inference for multivariate data. Here we introduce several general structures …

A data depth can be used to measure the “depth” or “outlyingness” of a given multivariate
sample with respect to its underlying distribution. This leads to a natural center-outward …

The statistical analysis of functional data is a growing need in many research areas. In
particular, a robust methodology is important to study curves, which are the output of many …

In practice, the use of functional data is often preferable to that of large finitedimensional
vectors obtained by discrete approximations of functions. In this paper a new concept of data …

Five notions of data depth are considered. They are mostly designed for functional data but
they can be also adapted to the standard multivariate case. The performance of these depth …

This article reviews the literature concerning supervised and unsupervised classification of
functional data. It first explains the meaning of unsupervised classification vs. supervised …

In financial distress analysis, the diagnosis of firms at risk for bankruptcy is crucial in
preparing to hedge against any financial damage the at-risk firms stand to inflict. Some pre …

In this article, we address the problem of mining and analyzing multivariate functional data.
That is, data where each observation is a set of possibly correlated functions. Complex data …

A robust cluster procedure for functional data is introduced. It is based on the notion of
impartial trimming. Existence and consistency results are obtained. Furthermore, a feasible …