Regression modelGIS / spatial

Panel Multiscale Geographically Weighted Regression (Panel MGWR)

Panel MGWR extends Multiscale Geographically Weighted Regression to repeated-observations (panel) data, allowing each predictor to operate at its own spatial bandwidth while controlling for unit-specific or time-specific fixed effects. It is used when both spatial heterogeneity and temporal structure matter simultaneously.

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Sources

  1. Fotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale Geographically Weighted Regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247-1265. DOI: 10.1080/24694452.2017.1352480
  2. Yu, H., Fotheringham, A. S., Li, Z., Oshan, T., Kang, W., & Wolf, L. J. (2020). Inference in Multiscale Geographically Weighted Regression. Geographical Analysis, 52(1), 87-106. DOI: 10.1111/gean.12189

Related methods

ScholarGatePanel Multiscale Geographically Weighted Regression (Panel Multiscale Geographically Weighted Regression). Retrieved 2026-06-04 from https://scholargate.app/en/spatial-analysis/panel-multiscale-geographically-weighted-regression