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Panel Multiscale Geographically Weighted Regression×الانحدار الجغرافي الموزون متعدد المقاييس (MGWR)×
المجالالتحليل المكانيالتحليل المكاني
العائلةRegression modelRegression model
سنة النشأة2017-20202017
صاحب الطريقةFotheringham, Yang & Kang (MGWR base); panel extension developed in spatial econometrics literatureA. Stewart Fotheringham, Wei Yang, and Wei Kang
النوعSpatially varying coefficient panel regressionLocal spatial regression
المصدر التأسيسيFotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale Geographically Weighted Regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247-1265. DOI ↗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 ↗
الأسماء البديلةPanel MGWR, MGWR panel data, multiscale GWR panel, panel spatially varying coefficient modelMGWR, multiscale GWR, multi-scale geographically weighted regression, variable-bandwidth GWR
ذات صلة55
الملخصPanel 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.Multiscale Geographically Weighted Regression (MGWR) is a local spatial regression framework that relaxes the single-bandwidth constraint of standard GWR by allowing each predictor to operate at its own spatial scale. Each coefficient surface is calibrated with its own bandwidth, enabling the model to distinguish drivers that vary slowly across space from those that vary sharply.
ScholarGateمجموعة البيانات
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  1. v1
  2. 2 المصادر
  3. PUBLISHED

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ScholarGateقارن الطرق: Panel Multiscale Geographically Weighted Regression · Multiscale Geographically Weighted Regression. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare