An early warning system for space-time cluster detection.
Autor(a) principal: | |
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Data de Publicação: | 2003 |
Outros Autores: | , |
Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFOP |
Texto Completo: | http://www.repositorio.ufop.br/handle/123456789/1789 |
Resumo: | A new topic of great relevance and concern has been the design of efficient early warning systems to detect as soon as possible the emergence of spatial clusters. In particular, many applications involving spatial events recorded as they occur sequentially in time require this kind of analysis, such as fire spots in forest areas as in the Amazon, crimes occurring in urban centers, locations of new disease cases to prevent epidemics, etc. We propose a statistical method to test for the presence of space-time clusters in point processes data, when the goal is to identify and evaluate the statistical significance of localized clusters. It is based on scanning the three dimensional space with a score test statistic under the null hypothesis that the point process is an inhomogeneous Poisson point process with space and time separable first order intensity. We discuss an algorithm to carry out the test and we illustrate our method with space-time crime data from Belo Horizonte, a large Brazilian city. |
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Assunção, Renato MartinsTavares, Andréa IabrudiKulldorff, Martin2012-11-13T17:35:02Z2012-11-13T17:35:02Z2003ASSUNÇÃO, R. M. ; TAVARES, A. I. KULLDORFF, M. An early warning system for space-time cluster detection. In. Brazilian Symposium on GeoInformatics - GEOINFO, 5,. 2003, Campos do Jordão. Anais... Campos do Jordão: Brazilian Symposium on GeoInformatics, 2003. Disponível em: <http://www.geoinfo.info/portuguese/geoinfo2003/papers/geoinfo2003-15.pdf>. Acesso em: 13 nov. 2012.http://www.repositorio.ufop.br/handle/123456789/1789A new topic of great relevance and concern has been the design of efficient early warning systems to detect as soon as possible the emergence of spatial clusters. In particular, many applications involving spatial events recorded as they occur sequentially in time require this kind of analysis, such as fire spots in forest areas as in the Amazon, crimes occurring in urban centers, locations of new disease cases to prevent epidemics, etc. We propose a statistical method to test for the presence of space-time clusters in point processes data, when the goal is to identify and evaluate the statistical significance of localized clusters. It is based on scanning the three dimensional space with a score test statistic under the null hypothesis that the point process is an inhomogeneous Poisson point process with space and time separable first order intensity. We discuss an algorithm to carry out the test and we illustrate our method with space-time crime data from Belo Horizonte, a large Brazilian city.An early warning system for space-time cluster detection.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectengreponame:Repositório Institucional da UFOPinstname:Universidade Federal de Ouro Preto (UFOP)instacron:UFOPinfo:eu-repo/semantics/openAccessLICENSElicense.txtlicense.txttext/plain; charset=utf-81748http://www.repositorio.ufop.br/bitstream/123456789/1789/2/license.txt8a4605be74aa9ea9d79846c1fba20a33MD52ORIGINALEVENTO_EarlyWarningSystem.pdfEVENTO_EarlyWarningSystem.pdfapplication/pdf224954http://www.repositorio.ufop.br/bitstream/123456789/1789/1/EVENTO_EarlyWarningSystem.pdfbc08a1903eaa42ae49004000bc8693d2MD51123456789/17892015-11-24 12:22:09.546oai:localhost: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Repositório InstitucionalPUBhttp://www.repositorio.ufop.br/oai/requestrepositorio@ufop.edu.bropendoar:32332015-11-24T17:22:09Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)false |
dc.title.pt_BR.fl_str_mv |
An early warning system for space-time cluster detection. |
title |
An early warning system for space-time cluster detection. |
spellingShingle |
An early warning system for space-time cluster detection. Assunção, Renato Martins |
title_short |
An early warning system for space-time cluster detection. |
title_full |
An early warning system for space-time cluster detection. |
title_fullStr |
An early warning system for space-time cluster detection. |
title_full_unstemmed |
An early warning system for space-time cluster detection. |
title_sort |
An early warning system for space-time cluster detection. |
author |
Assunção, Renato Martins |
author_facet |
Assunção, Renato Martins Tavares, Andréa Iabrudi Kulldorff, Martin |
author_role |
author |
author2 |
Tavares, Andréa Iabrudi Kulldorff, Martin |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Assunção, Renato Martins Tavares, Andréa Iabrudi Kulldorff, Martin |
description |
A new topic of great relevance and concern has been the design of efficient early warning systems to detect as soon as possible the emergence of spatial clusters. In particular, many applications involving spatial events recorded as they occur sequentially in time require this kind of analysis, such as fire spots in forest areas as in the Amazon, crimes occurring in urban centers, locations of new disease cases to prevent epidemics, etc. We propose a statistical method to test for the presence of space-time clusters in point processes data, when the goal is to identify and evaluate the statistical significance of localized clusters. It is based on scanning the three dimensional space with a score test statistic under the null hypothesis that the point process is an inhomogeneous Poisson point process with space and time separable first order intensity. We discuss an algorithm to carry out the test and we illustrate our method with space-time crime data from Belo Horizonte, a large Brazilian city. |
publishDate |
2003 |
dc.date.issued.fl_str_mv |
2003 |
dc.date.accessioned.fl_str_mv |
2012-11-13T17:35:02Z |
dc.date.available.fl_str_mv |
2012-11-13T17:35:02Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
ASSUNÇÃO, R. M. ; TAVARES, A. I. KULLDORFF, M. An early warning system for space-time cluster detection. In. Brazilian Symposium on GeoInformatics - GEOINFO, 5,. 2003, Campos do Jordão. Anais... Campos do Jordão: Brazilian Symposium on GeoInformatics, 2003. Disponível em: <http://www.geoinfo.info/portuguese/geoinfo2003/papers/geoinfo2003-15.pdf>. Acesso em: 13 nov. 2012. |
dc.identifier.uri.fl_str_mv |
http://www.repositorio.ufop.br/handle/123456789/1789 |
identifier_str_mv |
ASSUNÇÃO, R. M. ; TAVARES, A. I. KULLDORFF, M. An early warning system for space-time cluster detection. In. Brazilian Symposium on GeoInformatics - GEOINFO, 5,. 2003, Campos do Jordão. Anais... Campos do Jordão: Brazilian Symposium on GeoInformatics, 2003. Disponível em: <http://www.geoinfo.info/portuguese/geoinfo2003/papers/geoinfo2003-15.pdf>. Acesso em: 13 nov. 2012. |
url |
http://www.repositorio.ufop.br/handle/123456789/1789 |
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eng |
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eng |
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openAccess |
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