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Analysing regional industrialisation in Jiangsu province using geographically weighted regression
9 references·16 citing·41 second hop
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this work references cited by second hop

References

  • 1996Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity3,562 cited
  • 1998Geographically Weighted Regression: A Natural Evolution of the Expansion Method for Spatial Data Analysis1,154 cited
  • 1972Generating Models by the Expansion Method: Applications to Geographical Research*556 cited
  • 2000Statistical Tests for Spatial Nonstationarity Based on the Geographically Weighted Regression Model462 cited
  • 1994Chinese Township-Village Enterprises as Vaguely Defined Cooperatives345 cited
  • 1992Growth, Efficiency, and Convergence in China's State and Collective Industry316 cited
  • 1997Trends in quantitative methods I: stressing the local276 cited
  • 1994How Successful Has Chinese Enterprise Reform Been? Pitfalls in Opposite Biases and Focus206 cited
  • 1998Spatial Nonstationarity and Autoregressive Models176 cited

Cited by

  • 2011Modeling hotel room price with geographically weighted regression142 cited
  • 2020Energy transition at local level: Analyzing the role of peer effects and socio-economic factors on UK solar photovoltaic deployment136 cited
  • 2007Can Geographically Weighted Regressions Improve Regional Analysis and Policy Making?126 cited
  • 2010Regional effects of terrorism on economic growth in Turkey: A geographically weighted regression approach120 cited
  • 2004

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Using Geographically Weighted Regression Models to Estimate Annual Average Daily Traffic
115 cited
  • 2006Spatially varying development mechanisms in the Greater Beijing Area: a geographically weighted regression investigation114 cited
  • 2007Modeling Spatial Dimensions of Housing Prices in Milwaukee, WI110 cited
  • 2008Spatial data analysis of regional development in Greater Beijing, China, in a GIS environment106 cited
  • 2010Modelling hedonic residential rents for land use and transport simulation while considering spatial effects80 cited
  • 2012Geographically Weighted Quantile Regression ( GWQR ): An Application to U . S . Mortality Data74 cited
  • 2008Local Linear Estimation of Spatially Varying Coefficient Models: An Improvement on the Geographically Weighted Regression Technique73 cited
  • 2015Modeling spatial variation of explanatory factors of urban expansion of Kolkata: a geographically weighted regression approach71 cited
  • 2010Grid-enabling Geographically Weighted Regression: A Case Study of Participation in Higher Education in England68 cited
  • 2009Geographically weighted regression bandwidth selection and spatial autocorrelation: an empirical example using Chinese agriculture data65 cited
  • 2019Estimating land value uplift around light rail transit stations in Greater Kuala Lumpur: An empirical study based on geographically weighted regression (GWR)64 cited
  • 2007Modeling Owner-Occupied Single-Family House Values in the City of Milwaukee: A Geographically Weighted Regression Approach59 cited