Testing for local structure in spatiotemporal point pattern data
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http://dx.doi.org/10.1002/env.2463 |
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Títol
Testing for local structure in spatiotemporal point pattern dataData de publicació
2017-09-03Editor
WileyCita bibliogràfica
SIINO, Marianna; RODRÍGUEZ-CORTÉS, Francisco Javier; MATEU, Jorge; ADELFIO, Giada. Testing for local structure in spatiotemporal point pattern data. Environmetrics (2017), special issue onlineTipus de document
info:eu-repo/semantics/articleVersió de l'editorial
http://onlinelibrary.wiley.com/doi/10.1002/env.2463/epdfVersió
info:eu-repo/semantics/publishedVersionParaules clau / Matèries
Resum
The detection of clustering structure in a point pattern is one of themain focuses
of attention in spatiotemporal data mining. Indeed, statistical tools for clustering
detection and identification of individual ... [+]
The detection of clustering structure in a point pattern is one of themain focuses
of attention in spatiotemporal data mining. Indeed, statistical tools for clustering
detection and identification of individual events belonging to clusters
are welcome in epidemiology and seismology. Local second-order characteristics
provide information on how an event relates to nearby events. In this
work, we extend local indicators of spatial association (known as LISA functions)
to the spatiotemporal context (which will be then called LISTA functions).
These functions are then used to build local tests of clustering to analyse differences
in local spatiotemporal structures.We present a simulation study to assess
the performance of the testing procedure, and we apply this methodology to
earthquake data. [-]
Publicat a
Environmetrics (2017), Special issue onlineProyecto de investigación
1) Spanish Ministry of Economy and Competitiveness, Grant/Award Number: MTM2016-78917-R; 2) Italian Ministry of Education University and Research (MIUR)Drets d'accés
http://rightsstatements.org/vocab/CNE/1.0/
info:eu-repo/semantics/restrictedAccess
info:eu-repo/semantics/restrictedAccess
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