A generalized Mahalanobis distance for the classification of functional data

Andrea Ghiglietti, Francesca Ieva, Anna Maria Paganoni

Risultato della ricerca: Contributo in libroContributo a convegno


We present some asymptotic results on the distance between the means of samples of curves generated by independent continuous time stochastic processes in L2(T). The asymptotic results are based on mild assumptions on the moments of the processes, and there are no conditions on their probability distribution. The metrics we consider extends the Mahalanobis distance to L2(T) without any truncation on the first principal components. Applications in the context of classification of functional data are finally discussed.
Lingua originaleEnglish
Titolo della pubblicazione ospiteClassification and Data Analysis Group: Book of abstracts
Numero di pagine6
Stato di pubblicazionePubblicato - 2017
Pubblicato esternamente
EventoClassification and Data Analysis Group 2017 - Milano
Durata: 13 set 201715 set 2017


ConvegnoClassification and Data Analysis Group 2017


  • Distances in L2
  • Functiona Data
  • Two-sample problems


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