Open Conference Systems, 50th Scientific meeting of the Italian Statistical Society

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Functional linear models for the analysis of similarity of waveforms.
Francesca Di Salvo, Renata Rotondi, Giovanni Lanzano

Last modified: 2018-05-18


In seismology methods based on waveform similarity analysis are adopted
to identify sequences of events characterized by similar fault mechanism and propagation pattern. Seismic waves can be considered as spatially interdependent three dimensional curves depending on time and the waveform similarity analysis can be configured as a functional clustering approach, on the basis of which the membership is assessed by the shape of the temporal patterns. For providing qualitative extraction of the most important information from the recorded signals we propose an
integration of the metadata, related to the waves, as explicative variables of a functional linear models. The temporal patterns of this effects, as well as the residual component, are investigated in order to detect a cluster structure. The implemented clustering techniques are based on functional data depth.


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