ScholarGate
Assistent

Methoden vergleichen

Prüfen Sie die ausgewählten Methoden nebeneinander; abweichende Zeilen sind hervorgehoben.

Panel Multiscale Geographically Weighted Regression (Panel MGWR)×Geographisch gewichtete Regression (GWR)×
FachgebietRäumliche AnalyseRäumliche Analyse
FamilieRegression modelRegression model
Entstehungsjahr2017-20202002
UrheberFotheringham, Yang & Kang (MGWR base); panel extension developed in spatial econometrics literatureFotheringham, Brunsdon & Charlton
TypSpatially varying coefficient panel regressionLocal spatial regression
Wegweisende QuelleFotheringham, 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., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
AliasnamenPanel MGWR, MGWR panel data, multiscale GWR panel, panel spatially varying coefficient modelGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Verwandt55
ZusammenfassungPanel 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.Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships.
ScholarGateDatensatz
  1. v1
  2. 2 Quellen
  3. PUBLISHED
  1. v1
  2. 1 Quellen
  3. PUBLISHED

Zur Suche Folien herunterladen

ScholarGateMethoden vergleichen: Panel Multiscale Geographically Weighted Regression · Geographically Weighted Regression. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare