A Simulation-Based Study of Geographically Weighted Regression as a Method for Investigating Spatially Varying Relationships
By Antonio Páez, Steven Farber, David C. Wheeler. 2011
236 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Global and Planetary Change
View Paper: https://www.semanticscholar.org/paper/dee17c612d753fdde17d16bd9af40d1467977b0c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Binbin Lu
- Paul Harris
- Martin Charlton
- Chris Brunsdon
- Isabella Gollini
- Y. Yamagata
- Daisuke Murakami
- Takahiro Yoshida
In Global and Planetary Change
- Martin Charlton
- Binbin Lu
- Paul Harris
- Takahiro Yoshida
- Chris Brunsdon
- Daniel A. Griffith
- Jin Li
- Isabella Gollini
Citations in the corpus
- GWmodel: An R Package for Exploring Spatial Heterogeneity Using Geographically Weighted Models (2013, methodology): “…models Collinearity is a problem in any form of regression modelling and the importance of assessing and taking action has been raised by the many commentaries on local collinearity in GW regression (Wheeler and Tiefelsdorf 2005; Wheeler 2007, 2009, 2010, 2013a; Griffith 2008; Páez et al. 2011).”
- Tourism and regional income inequality: Evidence from China (2016, methodology): “Different approaches have been proposed to estimate the parameters of local models such as GWR (Páez et al., 2002; Yang & Fik, 2014) and SALE (Pace & LeSage, 2004).”
- A Moran coefficient-based mixed effects approach to investigate spatially varying relationships (2016, background): “First, the coefficients of 10 the basic GWR typically suffer from multicollinearity (Páez et al., 2011; Wheeler and 11 Tiefelsdorf, 2005).”
- Spatial interpolation methods applied in the environmental sciences: A review (2014, methodology): “The application of this method to spatial interpolation would be worthwhile (Wheeler and Páez, 2010); but its applications to environmental sciences are still rare (Harris et al., 2011) and should be cautiously exercised particularly when sample size is small (Páez et al., 2011).”
- Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria (2014, background): “Recently, Páez et al. (2011) mitigate the doubt not to use GWR for inference.”