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Panel Multiscale Geographically Weighted Regression/Ushahidi
Rekodi ya ushahidi wa mbinu

Panel Multiscale Geographically Weighted Regression

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.

Sources recorded, not reviewed

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Panel Multiscale Geographically Weighted Regression
Rekodi ya mbinu ya kiajenda · regression-model / spatial-analysis
  • 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
  • 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
Fungua mbinu kamili

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Zilizotengenezwa kutoka kwa grafu ya mbinu na kuonyeshwa kama uhusiano uliopendekezwa na mashine — hakuna dai la ushahidi linalodokezwa.

Same method familyGeographically Weighted Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketLocal Geographically Weighted Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMultiscale Geographically Weighted Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPanel Spatial Durbin Modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketPanel Spatial Error Modelmachine-suggested · Relational suggestion, not evidence.

Hali ya ushahidi

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

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