Details of Research Outputs

Status已发表Published
TitleA note on the mixed geographically weighted regression model
Creator
Date Issued2004
Source PublicationJournal of Regional Science
ISSN0022-4146
Volume44Issue: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.

DOI10.1111/j.1085-9489.2004.00331.x
URLView source
Indexed BySCIE
Language英语English
WOS Research AreaBusiness & Economics ; Environmental Sciences & Ecology ; Public Administration
WOS SubjectEconomics ; Environmental Studies ; Regional & Urban Planning
WOS IDWOS:000189024500007
Scopus ID2-s2.0-1642264983
Citation statistics
Cited Times:58[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/2450
CollectionResearch outside affiliated institution
Corresponding AuthorMei, 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.
Files in This Item:
There are no files associated with this item.
Related Services
Usage statistics
Google Scholar
Similar articles in Google Scholar
[Mei, Changlin]'s Articles
[He, Shuyuan]'s Articles
[Fang, Kaitai]'s Articles
Baidu academic
Similar articles in Baidu academic
[Mei, Changlin]'s Articles
[He, Shuyuan]'s Articles
[Fang, Kaitai]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Mei, Changlin]'s Articles
[He, Shuyuan]'s Articles
[Fang, Kaitai]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.