ScholarGate
Assistent

Methoden vergleichen

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

Geographisch gewichtete Regression (GWR)×LISA – Lokale Indikatoren räumlicher Assoziation (Local Moran's I)×
FachgebietRäumliche AnalyseRäumliche Analyse
FamilieRegression modelRegression model
Entstehungsjahr20021995
UrheberFotheringham, Brunsdon & CharltonLuc Anselin
TypLocal spatial regressionLocal spatial autocorrelation statistic
Wegweisende QuelleFotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗
AliasnamenGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)local Moran's I, local spatial autocorrelation, LISA cluster analysis, LISA — Yerel Uzamsal Otokorelasyon (Local Moran's I)
Verwandt55
ZusammenfassungGeographically 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.LISA, introduced by Luc Anselin in 1995, is a local statistic that computes spatial autocorrelation separately for every observation rather than for the map as a whole. It pinpoints where high or low values cluster and where spatial outliers sit, decomposing the global Moran's I into a contribution from each location.
ScholarGateDatensatz
  1. v1
  2. 1 Quellen
  3. PUBLISHED
  1. v1
  2. 1 Quellen
  3. PUBLISHED

Zur Suche Folien herunterladen

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