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.
Siino M, Rodríguez‐Cortés FJ, Mateu J, & Adelfio G (2020). Spatio-temporal classification in point patterns under the presence of clutter. ENVIRONMETRICS, 31(2).
Data di pubblicazione: | 2020 |
Titolo: | Spatio-temporal classification in point patterns under the presence of clutter |
Autori: | ADELFIO, Giada (Corresponding) |
Citazione: | Siino M, Rodríguez‐Cortés FJ, Mateu J, & Adelfio G (2020). Spatio-temporal classification in point patterns under the presence of clutter. ENVIRONMETRICS, 31(2). |
Rivista: | |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1002/env.2599 |
Abstract: | 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. |
Settore Scientifico Disciplinare: | Settore SECS-S/01 - Statistica |
Appare nelle tipologie: | 1.01 Articolo in rivista |
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Siino_et_al-2019-Environmetrics.pdf | Versione Editoriale | Administrator Richiedi una copia | ||
GiadaAdelfio _Paper_submitted.pdf | Pre-print | Open Access Visualizza/Apri |