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dc.contributor.authorDuarte, Anderson Ribeiro-
dc.contributor.authorSilva, Spencer Barbosa da-
dc.contributor.authorOliveira, Fernando Luiz Pereira de-
dc.contributor.authorAlmeida, Alexandre Celestino Leite de-
dc.contributor.authorDuczmal, Luiz Henrique-
dc.date.accessioned2022-03-03T18:40:46Z-
dc.date.available2022-03-03T18:40:46Z-
dc.date.issued2021pt_BR
dc.identifier.citationDUARTE, A. R. et al. Space-time border analysis to evaluate and detect clusters. Communications in Statistics-Simulation and Computation, 2021. Disponível em: <https://www.tandfonline.com/doi/abs/10.1080/03610918.2021.1914094?journalCode=lssp20>. Acesso em: 25 ago. 2021.pt_BR
dc.identifier.issn1532-4141-
dc.identifier.urihttp://www.repositorio.ufop.br/jspui/handle/123456789/14618-
dc.description.abstractThis article presents a statistic to identify the proportional intensity of an area to belong to a space-time cluster, which is very important in spatial statistics. A significant extension of the so-called F-function has been described in detail, which, associated with new technology, allows the evaluation of the intensity of change moments in the time process and outline possible occurrences of clusters. The justification of the study is performed through an extensive review of the current literature of the area. The developed algorithms are detailed via computational experiments with simulated data. Real situations are presented and discussed in detail. Finally, topics for future research are indicated.pt_BR
dc.language.isoen_USpt_BR
dc.rightsrestritopt_BR
dc.subjectF-functionpt_BR
dc.subjectScan statisticspt_BR
dc.subjectClusters designpt_BR
dc.subjectAlarm for emerging clusterspt_BR
dc.titleSpace-time border analysis to evaluate and detect clusters.pt_BR
dc.typeArtigo publicado em periodicopt_BR
dc.identifier.uri2https://www.tandfonline.com/doi/abs/10.1080/03610918.2021.1914094?journalCode=lssp20pt_BR
dc.identifier.doihttps://doi.org/10.1080/03610918.2021.1914094pt_BR
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