Analysing highly complex and highly structured point patterns in space
Metadatos
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https://doi.org/10.1016/j.spasta.2017.04.007 |
Metadatos
Título
Analysing highly complex and highly structured point patterns in spaceFecha de publicación
2017Editor
ElsevierISSN
2211-6753Cita bibliográfica
ECKARDT, Matthias; MATEU, Jorge. Analysing highly complex and highly structured point patterns in space. Spatial Statistics, 2017Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.sciencedirect.com/science/article/pii/S2211675316301269Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
The purpose of this paper is to discuss two recently introduced approaches that focus on structures of different events that occur randomly in space: spatial dependence graph models (SDGMs), and network intensity ... [+]
The purpose of this paper is to discuss two recently introduced approaches that focus on structures of different events that occur randomly in space: spatial dependence graph models (SDGMs), and network intensity functions. While SDGMs are undirected graphical models which capture the conditional independence structure between components of multivariate spatial point processes, network intensity functions describe the first-order properties of point patterns that occur on arbitrary network structures. [-]
Publicado en
Spatial Statistics, 2017Proyecto de investigación
J. Mateu has been partially granted by grants MTM2013-43917-P, MTM2016-78917-R and P1-1B2015-40.Derechos de acceso
© 2017 Elsevier B.V. All rights reserved.
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