Title: Robustness on big functional data depths
Authors: Alicia Nieto-Reyes - Universidad de Cantabria (Spain) [presenting]
John Aston - University of Cambridge (United Kingdom)
Abstract: Functional depth ranks the data in a functional data set. We compare through simulations the robustness of several computationally efficient functional depths that can be applied in the big data setting. In turns, we see that the notion of depth that satisfies the properties of statistical functional depth results in a better performance under the presence of outliers.