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http://dx.doi.org/10.7465/jkdi.2017.28.1.173

Application of geographical and temporal weighted regression model to the determination of house price  

Park, Saehee (Department of Statistics, Chonnam National University)
Kim, Minsoo (Department of Statistics, Chonnam National University)
Baek, Jangsun (Department of Statistics, Chonnam National University)
Publication Information
Journal of the Korean Data and Information Science Society / v.28, no.1, 2017 , pp. 173-183 More about this Journal
Abstract
We investigate the factors affecting the price of apartments using the spatial and temporal data of private real estate prices. The factors affecting the price of apartment were analyzed using geographical and temporal weighted regression (GTWR) model which incorporates the temporal and spatial variation. In contrast to the OLS, a general approach used in previous studies, and GWR method which is most widely used for analyzing spatial data, GTWR considers both temporal and spatial characteristics of the house price, and leads to better description of the house price determination. Year of construction and floor area are selected as the significant factors from the analysis, and the house price are affected by them temporally and geographically.
Keywords
Geographical and temporal weighted regression; geographically weighted regression; spatial nonstaionarity; temporal nonstationarity;
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Times Cited By KSCI : 2  (Citation Analysis)
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