Multiscale Geographically Weighted Regression (MGWR)
MGWR provides a Windows and macOS interface for calibrating multiscale geographically weighted regression models so you can explore how multi-scale relationships vary across space.
MGWR GUI (Windows)
Windows | 64-bit
Version 2.2.1
Installer package with the latest stable build, examples, and documentation for Windows 10/11 environments.
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MGWR GUI (macOS)
macOS | Universal
Version 2.2.1
Universal binary for Apple Silicon and Intel Macs with notarized installer and starter projects.
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- Fotheringham, A. S., Oshan, T. M., & Li, Z. (2023). Multiscale geographically weighted regression: Theory and practice. CRC Press. Access
- Fotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale geographically weighted regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247-1265. Access
- Oshan, T. M., Li, Z., Kang, W., Wolf, L. J., & Fotheringham, A. S. (2019). mgwr: A Python implementation of multiscale geographically weighted regression for investigating process spatial heterogeneity and scale. ISPRS International Journal of Geo-Information, 8(6), 269. Access