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Spatial Hedonic Modeling using Geographically Weighted LASSO Model
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GWL을 적용한 공간 헤도닉 모델링

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Type
Academic journal
Author
Chanwoo Jin (서울대학교) Gunhak Lee (서울대학교)
Journal
The Korean Geographlcal Society Journal of the Korean Geographical Society Vol.49 No.6 KCI Excellent Accredited Journal
Published
2014.12
Pages
917 - 934 (18page)

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Result
Spatial Hedonic Modeling using Geographically Weighted LASSO Model
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Geographically weighted regression(GWR) model has been widely used to estimate spatially heterogeneous real estate prices. The GWR model, however, has some limitations of the selection of different price determinants over space and the restricted number of observations for local estimation. Alternatively, the geographically weighted LASSO(GWL) model has been recently introduced and received a growing interest. In this paper, we attempt to explore various local price determinants for the real estate by utilizing the GWL and its applicability to forecasting the real estate price. To do this, we developed the three hedonic models of OLS, GWR, and GWL focusing on the sales price of apartments in Seoul and compared those models in terms of model fit, prediction, and multicollinearity. As a result, local models appeared to be better than the global OLS on the whole, and in particular, the GWL appeared to be more explanatory and predictable than other models. Moreover, the GWL enabled to provide spatially different sets of price determinants which no multicollinearity exists. The GWL helps select the significant sets of independent variables from a high dimensional dataset, and hence will be a useful technique for large and complex spatial big data.

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요약
Abstract
1. 서론
2. 방법론 리뷰
3. 사례 연구
4. 연구 결과
5. 결론
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UCI(KEPA) : I410-ECN-0101-2016-981-001055748