Selection of spatial regression model using point pattern analysis
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Shin, H.S. | - |
dc.contributor.author | Lee, S.-K. | - |
dc.contributor.author | Lee, B. | - |
dc.date.available | 2020-02-28T18:45:17Z | - |
dc.date.created | 2020-02-12 | - |
dc.date.issued | 2014 | - |
dc.identifier.issn | 1598-4850 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/13030 | - |
dc.description.abstract | When a spatial regression model that uses kernel density values as a dependent variable is applied to retail business data, a unique model cannot be selected because kernel density values change following kernel bandwidths. To overcome this problem, this paper suggests how to use the point pattern analysis, especially the L-index to select a unique spatial regression model. In this study, kernel density values of retail business are computed by the bandwidth, the distance of the maximum L-index and used as the dependent variable of spatial regression model. To test this procedure, we apply it to meeting room business data in Seoul, Korea. As a result, a spatial error model (SEM) is selected between two popular spatial regression models, a spatial lag model and a spatial error model. Also, a unique SEM based on the real distribution of retail business is selected. We confrm that there is a trade-off between the goodness of fit of the SEM and the real distribution of meeting room business over the bandwidth of maximum L-index. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | Korean Society of Surveying | - |
dc.relation.isPartOf | Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography | - |
dc.title | Selection of spatial regression model using point pattern analysis | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.doi | 10.7848/ksgpc.2014.32.3.225 | - |
dc.identifier.bibliographicCitation | Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography, v.32, no.3, pp.225 - 231 | - |
dc.identifier.kciid | ART001895357 | - |
dc.identifier.scopusid | 2-s2.0-84905487424 | - |
dc.citation.endPage | 231 | - |
dc.citation.startPage | 225 | - |
dc.citation.title | Journal of the Korean Society of Surveying Geodesy Photogrammetry and Cartography | - |
dc.citation.volume | 32 | - |
dc.citation.number | 3 | - |
dc.contributor.affiliatedAuthor | Shin, H.S. | - |
dc.contributor.affiliatedAuthor | Lee, S.-K. | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | Kernel density | - |
dc.subject.keywordAuthor | L-index | - |
dc.subject.keywordAuthor | Meeting room business | - |
dc.subject.keywordAuthor | Spatial error model | - |
dc.subject.keywordAuthor | Spatial regression model | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
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