A Note on the Mixed Geographically Weighted Regression Model.
A mixed, geographically weighted regression (GWR) model is useful in the situation where certain explanatory variables influencing the response are global while others are local. Undoubtedly, how to identify these two types of the explanatory variables is essential for building such a model. Neverth...
| Publicado en: | Journal of Regional Science Vol. 44; no. 1; pp. 143 - 158 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Wiley-Blackwell
February 2004
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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=513165563&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 513165563 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00224146 RSC jtl: Journal of Regional Science issn: 00224146 maglogo: N pubinfo: dt: February 2004 vid: 44 iid: 1 pid: 480 pub: Wiley-Blackwell artinfo: ui: 513165563 10.1111/j.1085-9489.2004.00331.x ppf: 143 ppct: 15 formats: tig: atl: A Note on the Mixed Geographically Weighted Regression Model. aug: au: Mei, Chang-Lin He, Shu-Yuan Fang, Kai-Tai su: Geography -- Methodology Geography -- Statistical methods Regression analysis sug: subj: Geography -- Methodology Geography -- Statistical methods Regression analysis ab: A mixed, geographically weighted regression (GWR) model is useful in the situation where certain explanatory variables influencing the response are global while others are local. Undoubtedly, how to identify these two types of the explanatory variables is essential for building such a model. Nevertheless, it seems that there has not been a formal way to achieve this task. Based on some work on the GWR technique and the distribution theory of quadratic forms in normal variables, a statistical test approach is suggested here to identify a mixed GWR model. Then, this note mainly focuses on simulation studies to examine the performance of the test and to provide some guidelines for performing the test in practice. The simulation studies demonstrate that the test works quite well and provides a feasible way to choose an appropriate mixed GWR model for a given data set. Reprinted by permission of the publisher. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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