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Multiscale Geographically Weighted Regression (MGWR)×Priestorový Durbinov model (SDM)×
OdborPriestorová analýzaPriestorová analýza
RodinaRegression modelRegression model
Rok vzniku20172009
TvorcaA. Stewart Fotheringham, Wei Yang, and Wei KangLeSage & Pace
TypLocal spatial regressionSpatial regression model
Pôvodný zdrojFotheringham, A. S., Yang, W., & Kang, W. (2017). Multiscale geographically weighted regression (MGWR). Annals of the American Association of Geographers, 107(6), 1247-1265. DOI ↗LeSage, J. & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press. DOI ↗
Ďalšie názvyMGWR, multiscale GWR, multi-scale geographically weighted regression, variable-bandwidth GWRSDM, spatial mixed model, uzamsal durbin modeli
Príbuzné55
ZhrnutieMultiscale 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.The Spatial Durbin Model is a general spatial regression model that includes a spatial lag of both the dependent variable (ρWy) and the explanatory variables (WXθ). Introduced as the recommended starting point by LeSage and Pace (2009), it nests the spatial autoregressive (SAR) and spatial error (SEM) models as special cases.
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ScholarGatePorovnať metódy: Multiscale Geographically Weighted Regression · Spatial Durbin Model. Získané 2026-06-18 z https://scholargate.app/sk/compare