Modeling Spatial Dimensions of Housing Prices in Milwaukee, WI

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A Big Data–Based Geographically Weighted Regression Model for Public Housing Prices: A Case Study in Singapore (2018, background): “Yu et al. (2007) discussed the status and the spatial effects in a hedonic pricing model with the support of spatial statistics, spatial econometrics, and geographic information systems (GIS), which have received increasing attention in past years.”
Modelling hedonic residential rents for land use and transport simulation while considering spatial effects (2010, methodology): “…adjusted R-square. is measure is useful and applied in GWR as well, but it is no longer applicable in spatial simultaneous autoregressive models (Yu et al. 2007, 1092). erefore, other measures such as residual sum of squares (RSS), sum of squared errors (SSE), maximum likelihood value, Log…”
Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria (2014, methodology): “This fact is usually neglected in GWR specifications (for example, Bitter et al., 2007; Yu et al., 2007; Hanink et al., 2010), resulting in inefficient estimates (Wei and Qi, 2012).”