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http://www.repositorio.ufop.br/jspui/handle/123456789/7180
Título: | MAD-STEC : a method for multiple automatic detection of space-time emerging clusters. |
Autor(es): | Veloso, Bráulio Miranda Correa, Thais Rotsen Prates, Marcos O. Oliveira, Gabriel F. Tavares, Andréa Iabrudi |
Palavras-chave: | Surveillance Point pattern Prospective space-time surveillance Space-time clustering |
Data do documento: | 2016 |
Referência: | VELOSO, B. M. MAD-STEC: a method for multiple automatic detection of space-time emerging clusters. Statistics and Computing, v. 1, p. 1-12, 2016. Disponível em: <http://link.springer.com/article/10.1007/s11222-016-9673-y>. Acesso em: 23 jan. 2017. |
Resumo: | Crime or disease surveillance commonly rely in space-time clustering methods to identify emerging patterns. The goal is to detect spatial-temporal clusters as soon as possible after its occurrence and to control the rate of false alarms. With this in mind, a spatio-temporal multiple cluster detection method was developed as an extension of a previous proposal based on a spatial version of the Shiryaev– Roberts statistic. Besides the capability of multiple cluster detection, the method have less input parameter than the previous proposal making its use more intuitive to practitioners. To evaluate the new methodology a simulation study is performed in several scenarios and enlighten many advantages of the proposed method. Finally, we present a case study to a crime data-set in Belo Horizonte, Brazil. |
URI: | http://www.repositorio.ufop.br/handle/123456789/7180 |
Link para o artigo: | http://link.springer.com/article/10.1007/s11222-016-9673-y |
DOI: | https://doi.org/10.1007/s11222-016-9673-y |
ISSN: | 1573-1375 |
Aparece nas coleções: | DECOM - Artigos publicados em periódicos |
Arquivos associados a este item:
Arquivo | Descrição | Tamanho | Formato | |
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ARTIGO_MADSTECMethod.pdf Until 2030-01-23 | 2,45 MB | Adobe PDF | Visualizar/Abrir |
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