Geographically Weighted Regression ©2012, Timothy, G. Gregoire, Yale University Last Revised: October 2012
Geographically Weighted Regression
1998 – Present
1. Misc. 1. Book Reviews. Technometrics, 48(1).
2. Misc. 2. Columbus OH crime data.
3. Misc. 3. Cross validation of bandwidth for generalized Geographically Weighted
Regression.
4. Misc. 4. Geographically weighted regression.
5. Misc. 5. Georgia census data set (Spatial Data Frame Polygons).
6. Misc. 6. Geographically Weighted Regression: A brief primer on Geographically Weighted
Regression.
7. Brunsdon, C., Fotheringham, S. and Charlton, M. (1998) “Geographically weighted
regression – modeling spatial non - stationarity”. The Statistician 47 (3): 431 – 443.
8. Fotheringham, A.S., Charlton, M.E. and Brunsdon, C. (1998) “Geographically weighted
regression: a natural evolution of the expansion method for spatial data analysis”.
Environmental and Planning A (30): 1905-1927.
9. Brunsdon, C., Aitkin, M., Fotheringham, S. and Charlton, M. (1999) “A Comparison of
Random Coefficient modelling and Geographically Weighted Regression for spatially nonstationary regression problems”. Geographical and Environmental Modelling 3(1): 47-62.
10. Brunsdon, C. (1999) “Some notes on Parametric significance tests for geographically
Weighted Regression”. Journal of Regional Science 39(3): 497-524.
11. Leung, Y., Mei, C.L. and Zhang, W.X. (2000) “Statistical tests for spatial nonstationarity
based on the geographically weighted regression”. Environment and Planning A (32): 9-32.
12. Leung, Y., Mei, C.L. and Zhang, W.X. (2000) “Testing for spatial autocorrelation among
the residuals of the geographically weighted regression”. Environment and Planning A (32):
871 – 890.
13. Fotheringham, A. S., Brunsdon, C., and Charlton, M. 2002. Geographically Weighted
Regression: the analysis of spatially varying relationships. Wiley: Chichester. 269 p.
Geographically Weighted Regression ©2012, Timothy, G. Gregoire, Yale University 14. Gelfand, A.E., Kim, H., Sirmans, C.F. and Banerjee, S. (2003) “Spatial modeling with
spatially varying coefficient processes”. Journal of the American Statistical Association
98(462): 387 - 396.
15. LeSage, J.P. (2003) “A Family of Geographically Weighted Regression Models”.
16. Zhang, L., Bi, H., Cheng, P. and Davis, C.J. (2003) “Modelling spatial variation in tree
diameter –height relationships”. Forest Ecology and Management 189: 317 – 329.
17. Fotheringham, A.S. and Brunsdon, C. (2004) “Some thoughts on inference in the analysis of
spatial data”. International Journal of Geographical Information Science 18(5): 447-457.
18. Zhang, L., Bi, H., Cheng, P. and Davis, C.J. (2004) “Modeling spatial variation in tree
diameter –height relationships”. Forest Ecology and Management 189: 317 – 329.
19. Zhang, L. and Shi, H. (2004) “Local Modelling of Tree Growth by Geographically
Weighted Regression”. Forest Science 50(2): 225 - 244.
20. Wheeler, D. and Tiefelsdorf. (2005) “Multicollinearity and correlation among local
regression coefficients in geographically weighted regression”. Journal of Geographical
system 7: 161-187.
21. Zhang, L. and Gove, J.H. (2005) “Spatial Assessment of Model Errors from Four
Regression Techniques”. Forest Science 51(4): 334 - 346.
22. Zhang, L., Gove, J.H. and Heath, L.S. (2005) “Spatial residual analysis of six modeling
techniques”. Ecological Modelling 186: 154 – 177.
23. Bivand, R. and Brunstad, R. (2006) “Regional growth in Western Europe: detecting spatial
misspecification using the R environment”. Papers in Regional Science 85(2): 277 - 297.
24. Shi, H., Zhang, L. and Liu, J. (2006) “A new spatial-attribute weighting function for
geographically weighted regression”. Canada Journal research 36: 996 – 1005.
25. Kimsey, M.J., Moore, J. and McDaniel, P. (2008) “A Geographically Weighted Regression
Analysis of Douglas –Fir Site Index in North Central Idaho”. Forest Science 54(3): 356 366.
26. Zhang, L., Ma, Z. and Guo, L. (2008) “Spatially assessing model errors of four regression
techniques for three types of forests stands”. Oxford Journals 81(2): 209 – 225.
27. Finley, A.O., Banerjee, S. and McRoberts, R.E. (2009) “Hierarchical spatial models for
predicting tree species assemblage across large domains”. Applied Statistics: 1 - 45.
Geographically Weighted Regression ©2012, Timothy, G. Gregoire, Yale University 28. Szymanowski, M. and Kryza, M. (2011) “Application of geographically weighted
regression for modeling the spatial structure of urban heat island in the city of Wroclaw
(SW Poland)”. Procedia Environmental Sciences (3): 87-92.
29. Lu, B., Charlton, M. and Fotheringham, A.S. (2011) “Geographically weighted regression
using a non-enclidean Distance metric with a study on London house price data”. Procedia
Environmental Sciences (7): 92-97.
30. Wheeler, D. (2011) “Geographically weighted regression with penalties and diagnostic
tools”. Environment and Planning A (39): 2464 – 2481.
31. Lu, J. and Zhang, L. (2012) “Geographically local linear mixed models for tree height –
diameter relationship”. Forest Science 58(1): 75 - 84.