MGWR Tools

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

Free and open source. Pick the build that matches your machine.

Version 2.2.1

Get the software

Windows

Windows 10 / 11 · 64-bit

Installer package with the latest stable build, examples, and documentation.

Download

macOS

Universal · Apple Silicon & Intel

Notarized universal binary for Apple Silicon and Intel Macs, bundled with starter projects.

Download

Documentation

Manuals, references, and the open-source Python package.

Sample datasets

Example datasets to try the software on.

Bibliography changelog

The (M)GWR bibliography is revised as new studies appear. Every edition we have published stays available below, so a citation to a specific release can always be traced back to the exact file.

Citation references

Please cite these articles when using the above software

Fotheringham, A. S., Oshan, T. M., & Li, Z. (2023). Multiscale geographically weighted regression: Theory and practice. CRC Press.
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Fotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale geographically weighted regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247-1265.
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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.
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