Mostrar el registro sencillo del ítem
Local inhomogeneous second-order characteristics for spatio-temporal point processes occurring on linear networks
dc.contributor.author | D'ANGELO, Nicoletta | |
dc.contributor.author | adelfio, giada | |
dc.contributor.author | Mateu, Jorge | |
dc.date.accessioned | 2022-10-28T18:07:38Z | |
dc.date.available | 2022-10-28T18:07:38Z | |
dc.date.issued | 2022 | |
dc.identifier.citation | D’ANGELO, Nicoletta; ADELFIO, Giada; MATEU, Jorge. Local inhomogeneous second-order characteristics for spatio-temporal point processes occurring on linear networks. Statistical Papers, 2022, p. 1-27 | ca_CA |
dc.identifier.issn | 0932-5026 | |
dc.identifier.issn | 1613-9798 | |
dc.identifier.uri | http://hdl.handle.net/10234/200656 | |
dc.description.abstract | Point processes on linear networks are increasingly being considered to analyse events occurring on particular network-based structures. In this paper, we extend Local Indicators of Spatio-Temporal Association (LISTA) functions to the non-Euclidean space of linear networks, allowing to obtain information on how events relate to nearby events. In particular, we propose the local version of two inhomogeneous second-order statistics for spatio-temporal point processes on linear networks, the K- and the pair correlation functions. We put particular emphasis on the local K-functions, deriving come theoretical results which enable us to show that these LISTA functions are useful for diagnostics of models specified on networks, and can be helpful to assess the goodness-of-fit of different spatio-temporal models fitted to point patterns occurring on linear networks. Our methods do not rely on any particular model assumption on the data, and thus they can be applied for whatever is the underlying model of the process. We finally present a real data analysis of traffic accidents in Medellin (Colombia). | ca_CA |
dc.format.extent | 27 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Springer | ca_CA |
dc.relation.isPartOf | Statistical Papers, 2022, p. 1-27 | ca_CA |
dc.rights | © The Author(s) 2022 This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. | ca_CA |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | ca_CA |
dc.subject | linear networks | ca_CA |
dc.subject | Local Indicators of Spatio-Temporal Association | ca_CA |
dc.subject | local properties | ca_CA |
dc.subject | residual analysis | ca_CA |
dc.subject | second-order characteristics | ca_CA |
dc.subject | spatio-temporal point patterns | ca_CA |
dc.title | Local inhomogeneous second-order characteristics for spatio-temporal point processes occurring on linear networks | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.1007/s00362-022-01338-4 | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.relation.publisherVersion | https://link.springer.com/article/10.1007/s00362-022-01338-4#Fun | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
project.funder.name | Università degli Studi di Palermo | ca_CA |
Ficheros en el ítem
Este ítem aparece en la(s) siguiente(s) colección(ones)
-
INIT_Articles [752]
-
MAT_Articles [765]
Articles de publicacions periòdiques
Excepto si se señala otra cosa, la licencia del ítem se describe como: © The Author(s) 2022
This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give
appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence,
and indicate if changes were made. The images or other third party material in this article are included
in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If
material is not included in the article’s Creative Commons licence and your intended use is not permitted
by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the
copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.