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Prostorová autokorelace×Geograficky vážená regrese (GWR)×
OborProstorová analýzaProstorová analýza
RodinaRegression modelRegression model
Rok vzniku19502002
TvůrceP. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995)Fotheringham, Brunsdon & Charlton
TypSpatial statistic / exploratory spatial data analysisLocal spatial regression
Původní zdrojMoran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Další názvyspatial dependence, geographic autocorrelation, spatial clustering measure, SAGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Příbuzné55
ShrnutíSpatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations.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.
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ScholarGatePorovnat metody: Spatial Autocorrelation · Geographically Weighted Regression. Získáno 2026-06-18 z https://scholargate.app/cs/compare