Title: Analyzing high-dimensional functional data
Authors: Ana Arribas-Gil - Universidad Carlos III de Madrid (Spain)
Juan Romo - Universidad Carlos III de Madrid (Spain) [presenting]
Abstract: Functional data not only arrive as one-dimensional collections, but also as multivariate samples of curves or even as high- dimensional functional data sets. The concept of depth provides convenient tools for the robust analysis of curves. It allows to establish the notion of centrality and extremality and provides fundamentals for testing or classification. We analyze depth for high-dimensional functional data and apply these ideas to simulated high-dimensional samples of curves and to real high-dimensional functional observations.