On new families of anisotropic spatial log-Gaussian Cox processes
comunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7037
comunitat-uji-handle3:10234/8635
comunitat-uji-handle4:
INVESTIGACIONEste recurso está restringido
https://doi.org/10.1007/s00477-020-01906-w |
Metadatos
Título
On new families of anisotropic spatial log-Gaussian Cox processesFecha de publicación
2020Editor
SpringerISSN
1436-3240; 1436-3259Cita bibliográfica
NASIRZADEH, Fariba; SHISHEBOR, Zohreh; MATEU, Jorge. On new families of anisotropic spatial log-Gaussian Cox processes. Stochastic Environmental Research and Risk Assessment, 2020, p. 1-31Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://link.springer.com/article/10.1007/s00477-020-01906-wVersión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Cox processes are natural models for point process phenomena that are environmentally driven, but much less natural for phenomena driven primarily by interactions amongst the points. The class of log-Gaussian Cox ... [+]
Cox processes are natural models for point process phenomena that are environmentally driven, but much less natural for phenomena driven primarily by interactions amongst the points. The class of log-Gaussian Cox processes (LGCPs) has an elegant simplicity, and one of its attractive features is the tractability of the multivariate normal distribution carries over, to some extent, to the associated Cox process. In the statistical analysis of spatial point patterns, it is often assumed isotropy because of a simpler interpretation and ease of analysis. However, there are many cases in which the spatial structure depends on the direction. In this paper, we introduce new families of anisotropic spatial LGCPs that are useful to model spatial anisotropic point patterns that exhibit a degree of clustering. We propose classes of families consisting of elliptical and non-elliptical models. The former can be reduced to isotropic forms after some rotations, while the latter family goes beyond this property. We derive analytical forms for the covariance of the associated random field, and some second-order characteristics. A moment-based estimation procedure is followed to make inference on the parameters that control the degree of anisotropy. The estimation procedure is evaluated through a simulation study under a variety of scenarios and various degrees of anisotropy. Our methodology is illustrated on two real datasets of earthquakes in South America and the Mediterranean Europe. [-]
Publicado en
Stochastic Environmental Research and Risk Assessment, 2020, p. 1-31Entidad financiadora
Ministerio de Economía y Competitividad
Código del proyecto o subvención
P1-1B2015-40 | UJI-B2018-04 | MTM2016-78917-R
Derechos de acceso
© Springer-Verlag GmbH Germany, part of Springer Nature 2020
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/restrictedAccess
http://rightsstatements.org/vocab/InC/1.0/
info:eu-repo/semantics/restrictedAccess
Aparece en las colecciones
- INIT_Articles [754]
- MAT_Articles [766]