A1323
Title: Embedding zero-inflated data: A Hilbert space PCA approach
Authors: Enea Bongiorno - Universita del Piemonte Orientale (Italy) [presenting]
Giacomo Aletti - University of Milan (Italy)
Abstract: A novel principal component analysis method for concentration curves associated with non-negative and zero-inflated random variables is introduced. The proposed methodology relies on a diffeomorphic embedding of these curves into a suitable functional space with a Hilbert structure. This embedding not only enables the use of well-established techniques for Hilbert spaces, but also facilitates the interpretation of the resulting components.
