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Geographically Weighted Regression
Abstract
In regression models where the cases are geographical locations, sometimes regression coefficients do not remain fixed over space. A technique for exploring this phenomenon, geographically weighted regression is introduced. A related Monte Carlo significance test for spatial non-stationarity is also considered. Finally, an example of the method is given, using limiting long-term illness data from the 1991 UK census.
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Cited by
F. Dormann, C., M. McPherson, J., B. Araújo, M., Bivand, R., Bolliger, J., Carl, G., G. Davies, R., Hirzel, A., Jetz, W., Daniel Kissling, W., et al. (2007) · Ecography · doi:10.1111/j.2007.0906-7590.05171.x · Cited by 3,433
Large mesopelagic fishes biomass and trophic efficiency in the open ocean
Irigoien, X., Klevjer, T. A., Røstad, A., Martinez, U., Boyra, G., Acuña, J. L., Bode, A., Echevarria, F., Gonzalez-Gordillo, J. I., Hernandez-Leon, S., et al. (2014) · Nature Communications · doi:10.1038/ncomms4271 · Cited by 813
Relationships between Human Population Density and Burned Area at Continental and Global Scales
Bistinas, I., Oom, D., Sá, A. C. L., Harrison, S. P., Prentice, I. C., & Pereira, J. M. C. (2013) · PLoS ONE · doi:10.1371/journal.pone.0081188 · Cited by 110
Locally-adaptive slip prediction for planetary rovers using Gaussian processes
Cunningham, C., Ono, M., Nesnas, I., Yen, J., & Whittaker, W. L. (2017) · 2017 IEEE International Conference on Robotics and Automation (ICRA) · doi:10.1109/icra.2017.7989646 · Cited by 51
Combining Property Price Predictions from Repeat Sales and Spatially Enhanced Hedonic Regressions
Oust, A., Hansen, S. N., & Pettrem, T. R. (2020) · The Journal of Real Estate Finance and Economics · doi:10.1007/s11146-019-09723-x · Cited by 33
Metadata
- Authors
- Brunsdon, C., Fotheringham, S., & Charlton, M.
- Venue
- Journal of the Royal Statistical Society: Series D (The Statistician)
- Publisher
- Wiley
- Published
- 1998-09
- Volume
- 47
- Issue
- 3
- Pages
- 431-443
- ISSN
- 0039-0526 (ISSN-L)
- 1467-9884
- OpenAlex
- W2045066934
- Cited by
- 1,563
- References
- 0
- FWCI
- 8.57
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Geographically Weighted Regression. https://app.cochat.ai/papers/10.1111/1467-9884.00145
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- Brunsdon, C., Fotheringham, S., & Charlton, M. (1998). Geographically Weighted Regression. Journal of the Royal Statistical Society: Series D (The Statistician). https://doi.org/10.1111/1467-9884.00145
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
