58 citations · 88 across the 3 of their papers we have counts for
5 papers
A notion of depth for sparse functional data
Carlo Sguera, Sara López-Pintado
Data depth is a well-known and useful nonparametric tool for analyzing functional data. It provides a novel way of ranking a sample of curves from the center outwards and defining…
Detecting and Classifying Outliers in Big Functional Data
Oluwasegun Taiwo Ojo, Antonio Fernández Anta, Rosa E. Lillo +1
We propose two new outlier detection methods, for identifying and classifying different types of outliers in (big) functional data sets. The proposed methods are based on an existi…
An empirical comparison of global and local functional depths
Carlo Sguera, Rosa E. Lillo
A functional data depth provides a center-outward ordering criterion which allows the definition of measures such as median, trimmed means, central regions or ranks in a functional…
Functional outlier detection by a local depth with application to NOx levels
Carlo Sguera, Pedro Galeano, Rosa Lillo
This paper proposes methods to detect outliers in functional data sets and the task of identifying atypical curves is carried out using the recently proposed kernelized functional…
Spatial Depth-Based Classification for Functional Data
Carlo Sguera, Pedro Galeano, Rosa Lillo
We enlarge the number of available functional depths by introducing the kernelized functional spatial depth (KFSD). KFSD is a local-oriented and kernel-based version of the recentl…