Testing the Importance of the Explanatory Variables in a Mixed Geographically Weighted Regression Model

By Changlin Mei, Ning Wang, Wenxiu Zhang. 2006

98 citations recorded by the source corpus.

Subfields: Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/5127a91a320a47619e6d6b449dc3519f8478e73a

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

1. Martin Charlton
2. Chris Brunsdon
3. Li Wang
4. Jingru Mu
5. Guannan Wang
6. Eric Vaz
7. Marco Helbich
8. Peter Nijkamp

Citations in the corpus

• Spatial Heterogeneity in Hedonic House Price Models: The Case of Austria (2014, methodology): “The MGWR calibration procedure can be achieved by a multi-step algorithm (Fotheringham et al., 2002), a two-step procedure (Mei et al., 2006), and a constrained type (Wei and Qi, 2012).”
• Semiparametric geographically weighted generalisedlinear modelling in GWR 4.0 (2009, background): “Mei et al. (2004; 2006) proposed F test schemes for this kind of model selection.”
• Estimation and inference in spatially varying coefficient models (2018, methodology): “For example, Mei, Wang, and Zhang (2006) used the bootstrap test to investigate the zero coefficients in a mixed GWR model, and Cai, Fan, and Yao (2000) proposed a new wild bootstrap test for the goodness of fit of the varying-coefficient models for nonlinear time series.”