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Metrics and barycenters for point pattern data
dc.contributor.author | Müller, Raoul | |
dc.contributor.author | Schuhmacher, Dominic | |
dc.contributor.author | Mateu, Jorge | |
dc.date.accessioned | 2020-10-21T13:22:58Z | |
dc.date.available | 2020-10-21T13:22:58Z | |
dc.date.issued | 2020 | |
dc.identifier.citation | MÜLLER, Raoul; SCHUHMACHER, Dominic; MATEU, Jorge. Metrics and barycenters for point pattern data. Statistics and Computing, 2020, p. 1-20 | ca_CA |
dc.identifier.issn | 0960-3174 | |
dc.identifier.issn | 1573-1375 | |
dc.identifier.uri | http://hdl.handle.net/10234/190063 | |
dc.description.abstract | We introduce the transport–transform and the relative transport–transform metrics between finite point patterns on a generalspace, which provide a unified framework for earlier point pattern metrics, in particular the generalized spike time and thenormalized and unnormalized optimal subpattern assignment metrics. Our main focus is on barycenters, i.e., minimizersof aq-th-order Fréchet functional with respect to these metrics. We present a heuristic algorithm that terminates in a localminimum and is shown to be fast and reliable in a simulation study. The algorithm serves as a general plug-in method that canbe applied to point patterns on any state space where an appropriate algorithm for solving the location problem for individualpoints is available. We present applications to geocoded data of crimes in Euclidean space and on a street network, illustratingthat barycenters serve as informative summary statistics. Our work is a first step toward statistical inference in covariate-basedmodels of repeated point pattern observations. | ca_CA |
dc.format.extent | 20 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Springer | ca_CA |
dc.relation.isPartOf | Statistics and Computing, 2020, p. 1-20 | ca_CA |
dc.rights | This article is licensed under a Creative CommonsAttribution 4.0 International License, which permits use, sharing, adap-tation, distribution and reproduction in any medium or format, aslong as you give appropriate credit to the original author(s) and thesource, provide a link to the Creative Commons licence, and indi-cate if changes were made. The images or other third party materialin this article are included in the article’s Creative Commons licence,unless indicated otherwise in a credit line to the material. If materialis not included in the article’s Creative Commons licence and yourintended use is not permitted by statutory regulation or exceeds thepermitteduse,youwillneedtoobtainpermissiondirectlyfromthecopy-right holder. © The Author(s) 2020 | ca_CA |
dc.rights.uri | http://creativecommons.org/licenses/by-sa/4.0/ | * |
dc.subject | Fréchet mean | ca_CA |
dc.subject | Fréchet median | ca_CA |
dc.subject | network | ca_CA |
dc.subject | optimal transport | ca_CA |
dc.subject | point process | ca_CA |
dc.subject | unbalanced | ca_CA |
dc.subject | wasserstein | ca_CA |
dc.title | Metrics and barycenters for point pattern data | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.1007/s11222-020-09932-y | |
dc.relation.projectID | Raoul Müller is supported byDeutsche ForschungsgemeinschaftGRK2088. Jorge Mateu is supported by MTM2016-78917-R from theSpanish Ministry of Economy and Competitiveness. Open Access funding provided by Projekt DEAL. | ca_CA |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.relation.publisherVersion | https://link.springer.com/article/10.1007/s11222-020-09932-y | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |
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Excepto si se señala otra cosa, la licencia del ítem se describe como: This article is licensed under a Creative CommonsAttribution 4.0 International License, which permits use, sharing, adap-tation, distribution and reproduction in any medium or format, aslong as you give appropriate credit to the original author(s) and thesource, provide a link to the Creative Commons licence, and indi-cate if changes were made. The images or other third party materialin this article are included in the article’s Creative Commons licence,unless indicated otherwise in a credit line to the material. If materialis not included in the article’s Creative Commons licence and yourintended use is not permitted by statutory regulation or exceeds thepermitteduse,youwillneedtoobtainpermissiondirectlyfromthecopy-right holder.
© The Author(s) 2020