Spatial cluster detection in mobility networks: a copula approach

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dc.contributor.authorKim, Heeyoungko
dc.contributor.authorDuan, Rongko
dc.contributor.authorKim, Sungilko
dc.contributor.authorLee, Jaehwanko
dc.contributor.authorMa, Guang-Qinko
dc.date.accessioned2019-01-23T05:50:49Z-
dc.date.available2019-01-23T05:50:49Z-
dc.date.created2019-01-07-
dc.date.issued2019-01-
dc.identifier.citationJOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, v.68, no.1, pp.99 - 120-
dc.identifier.issn0035-9254-
dc.identifier.urihttp://hdl.handle.net/10203/249796-
dc.description.abstractIn mobility network capacity planning, characterizing the mobility network traffic is one of the most challenging tasks. Besides the growth trend and multiple periodic temporal patterns for normal traffic, the problem is complicated by the occasionally intense traffic for special events and its dynamic spatial relationships. Identifying the areas that have different traffic patterns compared with their neighbouring areas is a problem of spatial hotspot detection. In the paper, a copula-based method is proposed: using a multivariate extreme value copula, the upper tail dependence of the traffic distributions of neighbouring cell towers is evaluated, and then a cluster of multiple time series (i.e. multiple cell towers) with high upper tail dependence is detected. The method proposed is validated by using synthetic data as well as real mobility traffic data.-
dc.languageEnglish-
dc.publisherWILEY-
dc.titleSpatial cluster detection in mobility networks: a copula approach-
dc.typeArticle-
dc.identifier.wosid000453687800005-
dc.identifier.scopusid2-s2.0-85052406609-
dc.type.rimsART-
dc.citation.volume68-
dc.citation.issue1-
dc.citation.beginningpage99-
dc.citation.endingpage120-
dc.citation.publicationnameJOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS-
dc.identifier.doi10.1111/rssc.12307-
dc.contributor.localauthorKim, Heeyoung-
dc.contributor.nonIdAuthorDuan, Rong-
dc.contributor.nonIdAuthorKim, Sungil-
dc.contributor.nonIdAuthorLee, Jaehwan-
dc.contributor.nonIdAuthorMa, Guang-Qin-
dc.description.isOpenAccessN-
dc.type.journalArticleArticle-
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