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Registro Completo |
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
24/09/2010 |
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Data da última atualização: |
18/10/2010 |
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Autoria: |
ASSUNÇÃO, R. M.; LOPES, D. L. |
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Afiliação: |
RENATO MARTINS ASSUNÇÃO, UFMG; DANILO OURENÇO LOPES, UFMG. |
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Título: |
Testing association between origin-destination spatial locations. |
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Ano de publicação: |
2007 |
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Fonte/Imprenta: |
In: DAVID JUNIOR, C. A.; MONTEIRO, A. M. V. (Ed.). Advances in Geoinformatics. Berlin: Springer-Verlag, 2007. |
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Páginas: |
p. 293-304. |
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Idioma: |
Inglês |
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Conteúdo: |
Point processes are probabilistic frameworks to analyze spatial patterns composed by random point features, called events, stored in GIS database. In a multivariate point process, the events are of two or more different types such as the locations of disease cases and a set of locations labelled as control individuals or as the positions of plants in a planar region labelled according to their species [2]. Usually, the spatial analysis of multivariate point processes is concerned with two questions. The first one concentrates on the comparison between the individual patterns of the component processes. Typically, the interest is to decide if one spatial pattern (such as the disease cases) has some degree of spatial clustering with respect to another spatial pattern (such as the controls’ pattern) (see [5]), perhaps identifying some putative sources of increased relative intensity ([3]; [4]). The second question concentrates on testing the independence of two (or more) point patterns and therefore attention is directed to the joint distribution of the processes [7]. It is common, for example, to test if the presence of an event of a certain type in a location either inhibits or stimulates the nearby presence of events of other types. |
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Palavras-Chave: |
Bivariate linked point patterns; Knox''s statistic; Modelo estocástico; Origin-destination locations; Stochastic model; Teste estatístico. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 01944naa a2200217 a 4500
001 1862881
005 2010-10-18
008 2007 bl uuuu u00u1 u #d
100 1 $aASSUNÇÃO, R. M.
245 $aTesting association between origin-destination spatial locations.
260 $c2007
300 $ap. 293-304.
520 $aPoint processes are probabilistic frameworks to analyze spatial patterns composed by random point features, called events, stored in GIS database. In a multivariate point process, the events are of two or more different types such as the locations of disease cases and a set of locations labelled as control individuals or as the positions of plants in a planar region labelled according to their species [2]. Usually, the spatial analysis of multivariate point processes is concerned with two questions. The first one concentrates on the comparison between the individual patterns of the component processes. Typically, the interest is to decide if one spatial pattern (such as the disease cases) has some degree of spatial clustering with respect to another spatial pattern (such as the controls’ pattern) (see [5]), perhaps identifying some putative sources of increased relative intensity ([3]; [4]). The second question concentrates on testing the independence of two (or more) point patterns and therefore attention is directed to the joint distribution of the processes [7]. It is common, for example, to test if the presence of an event of a certain type in a location either inhibits or stimulates the nearby presence of events of other types.
653 $aBivariate linked point patterns
653 $aKnox''s statistic
653 $aModelo estocástico
653 $aOrigin-destination locations
653 $aStochastic model
653 $aTeste estatístico
700 1 $aLOPES, D. L.
773 $tIn: DAVID JUNIOR, C. A.; MONTEIRO, A. M. V. (Ed.). Advances in Geoinformatics. Berlin: Springer-Verlag, 2007.
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Registro original: |
Embrapa Agricultura Digital (CNPTIA) |
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