Spatial point processes and neural networks: A convenient couple
Metadatos
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https://doi.org/10.1016/j.spasta.2022.100644 |
Metadatos
Título
Spatial point processes and neural networks: A convenient coupleFecha de publicación
2022Editor
ElsevierISSN
2211-6753Cita bibliográfica
MATEU, Jorge; JALILIAN, Abdollah. Spatial point processes and neural networks: A convenient couple. Spatial Statistics, 2022, p. 100644Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://www.sciencedirect.com/science/article/pii/S221167532200029XVersión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Different spatial point process models and techniques have been developed in the past decades to facilitate the statistical analysis of spatial point patterns. However, in some cases the spatial point process methodology ... [+]
Different spatial point process models and techniques have been developed in the past decades to facilitate the statistical analysis of spatial point patterns. However, in some cases the spatial point process methodology is scarce and no flexible models nor suitable statistical methods are available. For example, due to its complexity, the statistical analysis of spatial point patterns of several groups observed at a number of time instances has not been studied in-depth, and there are a few limited models and methods available for such data. In the present work, we provide a mathematical framework for coupling neural network methods with the statistical analysis of point patterns. In particular, we discuss an example of deep neural networks in the statistical analysis of highly multivariate spatial point patterns and provide a new strategy for building spatio-temporal point processes using variational autoencoder generative neural networks. [-]
Publicado en
Spatial Statistics, 2022, p. 100644Entidad financiadora
National Science Foundation | Center for Tropical Forest Science | Smithsonian Tropical Research Institute | John D. and Catherine T. MacArthur Foundation | Small World Institute Fund | Andrew W. Mellon Foundation
Código del proyecto o subvención
DEB-00753102 | DEB-0129874 | DEB-0346488 | DEB-0425651 | DEB-0640386 | DEB-7922197 | DEB-8206992 | DEB-8605042 | DEB-8906869 | DEB-9100058 | DEB-9221033 | DEB-9405933 | DEB-9615226 | DEB-9909347 | 021115 | 0212284 | 0212818 | NSFDEB021104 | OISE0314581
Derechos de acceso
© 2022 Elsevier B.V. All rights reserved.
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info:eu-repo/semantics/restrictedAccess
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