Status | 已发表Published |
Title | A note on the mixed geographically weighted regression model |
Creator | |
Date Issued | 2004 |
Source Publication | Journal of Regional Science
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ISSN | 0022-4146 |
Volume | 44Issue:1Pages:143-157 |
Abstract | 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. © Blackwell Publishing, Inc. 2004. |
DOI | 10.1111/j.1085-9489.2004.00331.x |
URL | View source |
Indexed By | SCIE |
Language | 英语English |
WOS Research Area | Business & Economics ; Environmental Sciences & Ecology ; Public Administration |
WOS Subject | Economics ; Environmental Studies ; Regional & Urban Planning |
WOS ID | WOS:000189024500007 |
Scopus ID | 2-s2.0-1642264983 |
Citation statistics | |
Document Type | Journal article |
Identifier | http://repository.uic.edu.cn/handle/39GCC9TT/2450 |
Collection | Research outside affiliated institution |
Corresponding Author | Mei, Changlin |
Affiliation | 1.Institute of Mathematics, Peking University, Beijing, China 2.School of Sciences, Xi'an Jiaotong University, Xi'an, Shaanxi, China 3.The Stat. Res./Consultancy Centre, Hong Kong Baptist University, Hong Kong, Hong Kong |
Recommended Citation GB/T 7714 | Mei, Changlin,He, Shuyuan,Fang, Kaitai. A note on the mixed geographically weighted regression model[J]. Journal of Regional Science, 2004, 44(1): 143-157. |
APA | Mei, Changlin, He, Shuyuan, & Fang, Kaitai. (2004). A note on the mixed geographically weighted regression model. Journal of Regional Science, 44(1), 143-157. |
MLA | Mei, Changlin,et al."A note on the mixed geographically weighted regression model". Journal of Regional Science 44.1(2004): 143-157. |
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