A clustering method for Hilbert functional data based on the Small Ball Probability

Post date: 10-Feb-2015 15:12:56

18 FEBBRAIO 2015, ore 11.00, Sala Riunioni Primo Piano

Relatore: Dott. Enea Bongiorno, UPO, DiSEI

Titolo: A clustering method for Hilbert functional data based on the Small Ball Probability

Abstract: In questo seminario prensenterò un metodo di clustering per dati funzionali basato sul concetto di Probabilità delle Piccole Bolle di un processo a valori in spazi funzionali. Visto l'audience tipicamente eterogeneo dei 6d6, la discussione enfatizzerà sin dall’inizio le ricadute sulle applicazioni (economiche e antropometriche).

Per completezza, di seguito aggiungo l'abstract più teorico del lavoro di riferimento (vedi bibliografia al fondo):

"In the present work, motivated by the definition of a clustering method for functional data, the small-ball probability (SmBP) of a Hilbert valued process is considered. In particular, asymptotic factorizations for the SmBP are rigorously established exploiting the Karhunen-Loéve expansion whose basis turns out to be the optimal one in controlling the approximation errors. In fact, as the radius of the ball tends to zero, the SmBP is asymptotically proportional to the joint density of an increasing number (with the radius) of principal components (PCs) evaluated at the center of the ball up to a factor depending only on the radius. As a consequence, the joint distribution of the first PCs provides a surrogate density of the process and, hence, in a very natural way, becomes the core in defining a density based unsupervised classification algorithm. To implement the latter, a non-parametric estimator for such joint density is introduced and it is proved that used estimated PCs does not affect the rate of convergence. Finally, after a discussion on the proposed clustering algorithm, as an illustration, an application to a real dataset is provided."

Keywords: density based clustering; Hilbert functional data; Karhunen-Loéve decomposition; kernel density estimate; small-ball probability

Co-Autori: A. Goia, DiSEI, UPO

Bibliografia:

E.Bongiorno, A.Goia (2015) A clustering method for Hilbert functional data based on the Small Ball Probability. Submitted. http://arxiv.org/abs/1501.04308