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Spatio-temporal classification in point patterns under the presence of clutter

  • Autori: Siino M; Rodríguez‐Cortés FJ; Mateu J; Adelfio G
  • Anno di pubblicazione: 2020
  • Tipologia: Articolo in rivista
  • Parole Chiave: clutter; earthquakes; EM algorithm; features; mixtures; nearest-neighbor distances; spatio-temporal point patterns;
  • OA Link:


We consider the problem of detection of features in the presence of clutter for spatio-temporal point patterns. In previous studies, related to the spatial context, Kth nearest-neighbor distances to classify points between clutter and features. In particular, a mixture of distributions whose parameters were estimated using an expectation-maximization algorithm. This paper extends this methodology to the spatio-temporal context by considering the properties of the spatio-temporal Kth nearest-neighbor distances. For this purpose, we make use of a couple of spatio-temporal distances, which are based on the Euclidean and the maximum norms. We show close forms for the probability distributions of such Kth nearest-neighbor distances and present an intensive simulation study together with an application to earthquakes.