On the estimation and testing of mixed geographically weighted regression models

Economic Modelling

Volumn 29, Issue 6, 2012, Pages 2615-2620

  Wei, Chuan Hua ^a   Qi, Fei ^a  

^a MINZU UNIVERSITY OF CHINA   (China)

Author keywords

Constrained estimators; Generalized F test; Linear constraints; Mixed geographically weighted regression; Two step estimation

Indexed keywords

EID: 84865995784     PISSN: 02649993     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.econmod.2012.08.015     Document Type: Article

References (24)

1. Casetti E. Generating models by the expansion method: applications to geographic research. Geographical Analysis 1972, 4:81-91.
2. Brunsdon C., Fotheringham A.S., Charlton M. Geographically weighted regression: a method for exploring spatial nonstationarity. Geographical Analysis 1996, 28:281-298.
3. Brunsdon C., Fotheringham A.S., Charlton M. Geographically weighted regression: modelling spatial nonstationarity. The Statistician 1998, 47:431-443.
4. Brunsdon C., Fotheringham A.S., Charlton M. Some notes on parametric significance tests for geographically weighted regression. Journal of Regional Science 1999, 39:497-524.
5. Foster S.A., Gorr W.L. An adaptive filter for estimating spatially varying parameters: application to modeling police hours spent in response to calls for service. Management Science 1986, 32:878-889.
6. Cleveland W.S., Devlin S.J. Locally weighted regression analysis by local fitting. Journal of the American Statistical Association 1988, 83(596):C610.
7. Fan J.Q., Huang T. Profile likelihood inferences on semiparametric varying-coefficient partially linear models. Bernoulli 2005, 11:1031-1057.
8. Fotheringham A.S., Charlton M., Brunsdon C. Two techniques for exploring non-stationarity in geographical data. Geographical System 1997, 4:59-82.
9. Fotheringham A.S., Charlton M., Brunsdon C. Geographically weighted regression: a natural evolution of the expansion method for spatial data analysis. Environment and Planning A 1998, 30:1905-1927.
10. Fotheringham A.S., Brunsdon C., Charlton M. Geographically Weighted Regression the Analysis of Spatial Varying Relationships 2002, Wiley, West Sussex.
11. Goldberger A.S. Econometric Theory 1964, Wiley, New York.
12. Goldstein H. Multilevel models in educational and social research 1987, Oxford University Press.
13. Gorr W.L., Olligschlaeger A.M. Weighted spatial adaptive filtering: Monte Carlo studies and application to illicit drug market modeling. Geographical Analysis 1994, 26:67-87.
14. Hastie T.J., Tibshirani R.J. Varying-coefficient models (with discussion). Journal of the Royal Statistical Society B 1993, 55:757-796.
15. Jones J.P., Casetti E. Applications of the Expansion Method 1992, Routledge.
16. Leung Y., Mei C.L., Zhang W.X. Statistical tests for spatial nonstationarity based on the geographically weighted regression model. Environment and Planning A 2000, 32:9-32.
17. Leung Y., Mei C.L., Zhang W.X. Testing for spatial autocorrelation among the residuals of the geographically weighted regression. Environment and Planning A 2000, 32:871-890.
18. McMillen D.P., Redfearn C.L. Estimation and hypothesis testing for nonparametric hedonic house price functions. Journal of Regional Science 2010, 50(712):C733.
19. Mei C.L., He S.Y., Fang K.T. A note on the mixed geographically weighted regression model. Journal of Regional Science 2004, 44:143-157.
20. Mei C.L., Wang N., Zhang W.X. Testing the importance of the explanatory variables in a mixed geographically weighted regression model. Environment and Planning A 2006, 38:587-598.
21. Páez A., Uchida T., Miyamoto K. A general framework for estimation and inference of geographically weighted regression models: 1. location-specific kernel bandwidths and a test for locational heterogeneity. Environment and Planning A 2002, 34:733-754.
22. Páez A., Uchida T., Miyamoto K. A general framework for estimation and inference of geographically weighted regression models: 2. spatial association and model specification tests. Environment and Planning A 2002, 34:883-904.
23. Rao C.R., Toutenburg H., Shalabh, Heumann C. Linear models and generalizations: least squares and alternatives 2008, Springer, Berlin.
24. Wheeler D.C. Simultaneous coefficient penalization and model selection in geographically weighted regression: the geographically weighted lasso. Environment and Planning A 2009, 41:722-742.