B. Pulido Bravo, R. E. Lillo Rodríguez, A. M. Franco Pereira
The analysis of functional data poses a challenging problem due to the inherent infinite-dimensionality of the data, which means that the number of observations, or data points for each function, can be potentially infinite. Additionally, working with multivariate functional data, where there are multiple functions that may be interrelated, adds an additional layer of complexity to the analysis. In such cases, it may be challenging to determine the appropriate order of the data and identify meaningful patterns and structures in the data.
In this work, we propose a different extension of the epigraph and the hypograph indexes that takes into account the relationship between the different dimensions. This new definition of the multivariate indexes is considered for clustering multivariate functional data. Finally, the results will be illustrated through simulated and real datasets.
Palabras clave: Multivariate functional data, functional data analysis, clustering, epigraph, hypograph
Programado
GT01.FDA1 Sesión Invitada
7 de noviembre de 2023 15:30
CC1: Auditorio