Volume 26 - Article 6 | Pages 151-166
Mapping the results of local statistics: Using geographically weighted regression
References
Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control 19(6): 716-723.
| Weblink | doi:10.1109/TAC.1974.1100705 |
| Download reference in | RIS | BibTeX |
Ali, K., Partridge, M.D. , and Olfert, M.R. (2007). Can geographically weighted regressions improve regional analysis and policy making? International Regional Science Review 30(3): 300-331.
| Weblink | doi:10.1177/0160017607301609 |
| Download reference in | RIS | BibTeX |
Benson, T., Chamberlin, J., and Rhinehart, I. (2005). An investigation of the spatial determinants of the local prevalence of poverty in rural Malawi. Washington DC: International Food Policy Research Institute.
| Download reference in | RIS | BibTeX |
Brewer, C.A. (1994). Color use guidelines for mapping and visualization. In: MacEachren, A. and Taylor, D.R.F. (eds.). Visualization in modern cartography. New York: Elsevier: 123-147.
| Download reference in | RIS | BibTeX |
Brewer, C.A. (1996). Guidelines for selecting colors for diverging schemes on maps. The Cartographic Journal 33(2): 79-86.
| Weblink | doi:10.1179/000870496787757221 |
| Download reference in | RIS | BibTeX |
Brunsdon, C., Fotheringham, A.S., and Charlton, M. (1998a). Spatial nonstationarity and autoregressive models. Environment and Planning A. 30(6): 957-973.
| Weblink | doi:10.1068/a300957 |
| Download reference in | RIS | BibTeX |
Brunsdon, C., Fotheringham, A.S., and Charlton, M. (1998b). Geographically weighted regression: modelling spatial non-stationarity. Journal of the Royal Statistical Society. Series D (The Statistician) 47(3): 431-443.
| Weblink | doi:10.1111/1467-9884.00145 |
| Download reference in | RIS | BibTeX |
Brunsdon, C., Fotheringham, A.S., and Charlton, M.E. (1996). Geographically weighted regression: A method for exploring spatial nonstationarity. Geographical Analysis 28(4): 281-298.
| Weblink | doi:10.1111/j.1538-4632.1996.tb00936.x |
| Download reference in | RIS | BibTeX |
Byrne, G., Charlton, M., and Fotheringham, S. (2009). Multiple dependent hypothesis tests in geographically weighted regression. In: Lees, B.G. and Laffan, S.W. (eds.). 10th International Conference on GeoComputation, UNSW, Sydney, November-December. .
| Weblink | http://www.biodiverse.unsw.edu.au/geocomputat ... |
| Download reference in | RIS | BibTeX |
Calvo, E. and Escolar, M. (2003). The local voter: A geographically weighted regression approach to ecological inference. American Journal of Political Science 47(1): 189-204.
| Weblink | doi:10.1111/1540-5907.00013 |
| Download reference in | RIS | BibTeX |
Chen, C.Y.-J., Den, W.-S., Yang, T.-C., and Matthews, S.A. (2012). A geographically weighted quantile regression approach for spatial data analysis: An application to county-level U.S. mortality data. Geographical Analysis 44(2): 134-150.
| Weblink | doi:10.1111/j.1538-4632.2012.00841.x |
| Download reference in | RIS | BibTeX |
Chen, V.Y.-J., Wu, P.-C., Yang, T.-C., and Su, H.-J. (2010). Examining non-stationary effects of social determinants on cardiovascular mortality after cold surges in Taiwan. Science of the Total Environment 408(9): 2042-2049.
| Weblink | doi:10.1016/j.scitotenv.2009.11.044 |
| Download reference in | RIS | BibTeX |
Chen, V.Y.-J. and Yang, T.-C. (2011). SAS macro programs for geographically weighted generalized linear modeling with spatial point data: Applications to health research. Computer Methods and Programs in Biomedicine .
| Weblink | doi:10.1016/j.cmpb.2011.10.006 |
| Download reference in | RIS | BibTeX |
Cho, S., Lambert, D.M., Kim, S.G., and Jung, S. (2009). Extreme coefficients in geographically weighted regression and their effects on mapping. GIScience and Remote Sensing 46(3): 273-288.
| Weblink | doi:10.2747/1548-1603.46.3.273 |
| Download reference in | RIS | BibTeX |
Cleveland, W.S. (1979). Robust locally weighted regression and smoothing scatterplots. Journal of the American Statistical Association 74(368): 829-836.
| Weblink | doi:10.2307/2286407 |
| Download reference in | RIS | BibTeX |
Cressie, N.A.C. (1993). Statistics for spatial data. New York, NY: John Willey & Sons.
| Download reference in | RIS | BibTeX |
Dunn, R. (1989). A dynamic approach to two-variable color mapping. The American Statistician 43(4): 245-252.
| Weblink | doi:10.2307/2685372 |
| Download reference in | RIS | BibTeX |
ESRI (2011). ArcGIS Desktop: Release 10. Redlands, CA: Environmental Systems Research Institute.
| Download reference in | RIS | BibTeX |
Eyton, J.R. (1984). Complementary-color, two-variable maps. Annals of the Association of American Geographers 74(3): 477-490.
| Weblink | doi:10.1111/j.1467-8306.1984.tb01469.x |
| Download reference in | RIS | BibTeX |
Foody, G.M. (2003). Geographical weighting as a further refinement to regression modelling: An example focused on the NDVI-rainfall relationship. Remote Sensing of the Environment 88(3): 283-293.
| Weblink | doi:10.1016/j.rse.2003.08.004 |
| Download reference in | RIS | BibTeX |
Fotheringham, A.S., Brunsdon, C., and Charlton, M.E. (1997). Two techniques for exploring non-stationarity in geographical data. Geographical Systems 4: 59-82.
| Download reference in | RIS | BibTeX |
Fotheringham, A.S., Brunsdon, C., and Charlton, M.E. (2002). Geographically weighted regression: The analysis of spatially varying relationship. New York, NY: Wiley.
| Download reference in | RIS | BibTeX |
Fotheringham, A.S., Charlton, M.E., and Brunsdon, C. (1998). Geographically weighted regression: a natural evolution of the expansion method for spatial data analysis. Environment and Planning A 30(11): 1905-1927.
| Weblink | doi:10.1068/a301905 |
| Download reference in | RIS | BibTeX |
Goodchild, M.F. and Janelle, D.G. (2004). Spatially integrated social science. New York, NY: Oxford University Press.
| Download reference in | RIS | BibTeX |
Goovaerts, P. (2005). Analysis and detection of health disparities using geostatistics and a space-time information system: The case of prostate cancer mortality in the United States, 1970-1994. Proceedings of GIS Planet 2005 (May 30-June 2, 2005, Estoril, Portugal).
| Download reference in | RIS | BibTeX |
Gregory, I.N. and Ell, P.S. (2005). Analyzing spatiotemporal change by use of National Historical Geographical Information Systems: Population change during and after the Great Irish Famine. Historical Methods 38(4): 149-167.
| Weblink | doi:10.3200/HMTS.38.4.149-167 |
| Download reference in | RIS | BibTeX |
Hope, A.C.A. (1968). A simplified Monte Carlo significance test procedure. Journal of the Royal Statistical Society: Series B (Methodological) 30(3): 582-598.
| Download reference in | RIS | BibTeX |
Huang, Y. and Leung, Y. (2002). Analyzing regional industrialization in Jiangsu province using geographically weighted regression. Journal of Geographical Systems 4(2): 233-249.
| Weblink | doi:10.1007/s101090200081 |
| Download reference in | RIS | BibTeX |
Jiang, B., Yao, X., and Wheeler, D.C. (2010). Visualizing and diagnosing coefficients from geographically weighted regression models. In: Sui, D.Z., Tietze, W., Claval, P., Gradus, Y., Park, S.O., and Wusten, H. (eds.). Geospatial analysis and modelling of urban structure and dynamics. Netherlands: Springer: 415-436.
| Weblink | doi:10.1007/978-90-481-8572-6 |
| Download reference in | RIS | BibTeX |
Jones, J.P.III. and Hanham, R.Q. (1995). Contingency, realism and the expansion method. Geographical Analysis 27(3): 185-207.
| Weblink | doi:10.1111/j.1538-4632.1995.tb00905.x |
| Download reference in | RIS | BibTeX |
Jordan, L.M. (2006). Religion and demography in the United States: A geographical analysis. [Ph.D. Thesis]. Boulder, Colorado: University of Colorado at Boulder, Department of Geography.
| Download reference in | RIS | BibTeX |
Lloyd, C. (2011). Local models for spatial analysis (Second Edition). In: Boca Raton, FL: CRC Press.
| Download reference in | RIS | BibTeX |
Longley, P.A. and Tobon, C. (2004). Spatial dependence and heterogeneity in patterns of hardship: An intra-urban analysis. Annals Association of American Geographers 94(3): 503-519.
| Weblink | doi:10.1111/j.1538-4632.1995.tb00905.x |
| Download reference in | RIS | BibTeX |
Mennis, J.L. (2006). Mapping the results of geographically weighted regression. The Cartographic Journal 43(2): 171-179.
| Weblink | doi:10.1179/000870406X114658 |
| Download reference in | RIS | BibTeX |
Mennis, J.L. and Jordan, L.M. (2005). The distribution of environmental equity: Exploring spatial nonstationarity in multivariate models of air toxic releases. Annals of the Association of American Geographers 95(2): 249-268.
| Weblink | doi:10.1111/j.1467-8306.2005.00459.x |
| Download reference in | RIS | BibTeX |
Nakaya, T., Fotheringham, A.S., Brunsdon, C., and Charlton, M. (2005). Geographically weighted Poisson regression for disease association mapping. Statistics in Medicine 24(17): 2695-2717.
| Weblink | doi:10.1002/sim.2129 |
| Download reference in | RIS | BibTeX |
National Center for Geocomputation (2009). Maynooth, Ireland: National University of Ireland.
| Weblink | http://ncg.nuim.ie/ncg/GWR/software.htm (Febu ... |
| Download reference in | RIS | BibTeX |
Olson, J.M. (1981). Spectrally encoded two-variable maps. Annals of the Association of American Geographers 71(2): 259-276.
| Weblink | doi:10.1111/j.1467-8306.1981.tb01352.x |
| Download reference in | RIS | BibTeX |
Páez, A., Farber, S., and Wheeler, D.C. (2011). A simulation-based study of geographically weighted regression as a method for investigating spatially varying relationships. Environment and Planning A 43(12): 2992-3010.
| Weblink | doi:10.1177/0042098008091491 |
| Download reference in | RIS | BibTeX |
Páez, A., Long, F., and Farber, S. (2008). Moving window approaches for hedonic price estimation: An empirical comparison of modelling techniques. Urban Studies 45(8): 1565-1581.
| Weblink | doi:10.1177/0042098008091491 |
| Download reference in | RIS | BibTeX |
Partridge, M.D. and Rickman, D.S. (2005). Persistent pockets of extreme American poverty: People or place based? Columbia, MO: Rural Poverty Research Center (RPRC). (Working Paper 05-02, Jaunary 2005).
| Download reference in | RIS | BibTeX |
R Development Core Team (2011). R: A language and environment for statistical computing [electronic resource]. Vienna, Austria: R Foundation for Statistical Computing.
| Weblink | http://www.R-project.org (February 1, 2012) |
| Download reference in | RIS | BibTeX |
Salas, C., Ene, L., Gregoire, T.G.E., Næsset, E., and Gobakken, T. (2010). Modelling tree diameter from airborne laser scanning derived variables: A comparison of spatial statistical models. Remote Sensing of Environment 114(6): 1277-1285.
| Weblink | doi:10.1016/j.rse.2010.01.020 |
| Download reference in | RIS | BibTeX |
SAS (2011). Cary, NC, USA: SAS Institute Inc.
| Download reference in | RIS | BibTeX |
Shoff, C., Yang, T.-C., and Matthews, S.A. (2011). What has geography got to do with it? Using GWR to explore place-specific associations with prenatal care utilization. GeoJournal .
| Weblink | doi:10.1007/s10708-010-9405-3 |
| Download reference in | RIS | BibTeX |
Tufte, E. (1983). The visual display of quantitative information. Cheshire, CT: Graphics Press.
| Download reference in | RIS | BibTeX |
Wheeler, D.C. (2007). Diagnostic tools and a remedial method for collinearity in geographically weighted regression. Environment and Planning A 39(10): 2464-2481.
| Weblink | doi:10.1068/a38325 |
| Download reference in | RIS | BibTeX |
Wheeler, D.C. (2009). Simultaneous coefficient penalization and model selection in geographically weighted regression: The geographically weighted lasso. Environment and Planning A 41(3): 722-742.
| Weblink | doi:10.1068/a40256 |
| Download reference in | RIS | BibTeX |
Wheeler, D.C. and Páez, A. (2010). Geographically weighted regression. In: Fischer, M.M. and Getis, A. (eds.). Handbook of applied spatial analysis: Software tools, methods and applications. Berlin and Heidelberg: Springer: 461-486.
| Weblink | doi:10.1007/978-3-642-03647-7_22 |
| Download reference in | RIS | BibTeX |
Wheeler, D.C. and Tiefelsdorf, M. (2005). Multicollinearity and correlation among local regression coefficients in geographically weighted regression. Journal of Geographical Systems 7(2): 161-187.
| Weblink | doi:10.1007/s10109-005-0155-6 |
| Download reference in | RIS | BibTeX |
Yang, T.-C., Teng, H.W., and Haran, M. (2009). The impacts of social capital on infant mortality in the U.S.: A spatial investigation. Applied Spatial Analysis and Policy 2(3): 211-227.
| Weblink | doi:10.1007/s12061-009-9025-9 |
| Download reference in | RIS | BibTeX |
Yang, T.-C., Wu, P.-C., V.Y.-J., Chen, and H.-J., Su (2009). Cold surge: A sudden and spatially varying threat to health? Science of the Total Environment 407(10): 3421-3424.
| Weblink | doi:10.1016/j.scitotenv.2008.12.044 |
| Download reference in | RIS | BibTeX |
Young, L.J. and C.A., Gotway (2010). Using geostatistical methods in the analysis of public health data: The final frontier? geoENV VII - Geostatistics for Environmental Applications 16: 89-98.
| Weblink | doi:10.1007/978-90-481-2322-3_8 |
| Download reference in | RIS | BibTeX |
Yu, D.-L. (2006). Spatially varying development mechanisms in the Greater Beijing area: A geographically weighted regression investigation. Annals of Regional Science 40(1): 173-190.
| Weblink | doi:10.1007/s00168-005-0038-2 |
| Download reference in | RIS | BibTeX |
Yu, D.-L., Y.D., Wei, and Wu, C. (2007). Modeling spatial dimensions of housing prices in Milwaukee, WI. Environment and Planning B: Planning and Design 34(6): 1085-1102.
| Weblink | doi:10.1068/b32119 |
| Download reference in | RIS | BibTeX |
Zhao, F. and Park, N. (2004). Using geographically weighted regression models to estimate annual average daily traffic. In: Transportation Research Record 1879. Washington, DC: Transportation Research Board, National Research Council: 99-107.
| Download reference in | RIS | BibTeX |