A general framework for estimation and inference of geographically weighted regression models: 2. Spatial association and model specific tests.
A development that casts geographically weighted regression (GWR) as a model of locational heterogeneity is presented in order to formulate a general model of spatial effects that includes as special cases GWR with a spatially lagged objective variable and GWR with spatial error autocorrelation. It...
| Publicado en: | Environment & Planning A Vol. 34; no. 5; pp. 883 - 905 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Pion Limited
May 2002
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=513138542&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 513138542 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 0308518X EPL jtl: Environment & Planning A issn: 0308518X maglogo: N pubinfo: dt: May 2002 vid: 34 iid: 5 pid: 1065 pub: Pion Limited artinfo: ui: 513138542 10.1068/a34133 ppf: 883 ppct: 22 formats: tig: atl: A general framework for estimation and inference of geographically weighted regression models: 2. Spatial association and model specific tests. aug: au: Páez, Antonio Uchida, Takashi Miyamoto, Kazuaki su: Spatial analysis (Statistics) Geography -- Methodology Geography -- Statistical methods Regression analysis sug: subj: Spatial analysis (Statistics) Geography -- Methodology Geography -- Statistical methods Regression analysis ab: A development that casts geographically weighted regression (GWR) as a model of locational heterogeneity is presented in order to formulate a general model of spatial effects that includes as special cases GWR with a spatially lagged objective variable and GWR with spatial error autocorrelation. It is indicated that such an approach allows derivation of formal tests against several forms of model misspecification. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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