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Váženie inverznou priestorovou pravdepodobnosťou (Spatial IPW)×Geograficky vážená regresia (GWR)×
OdborKauzálna inferenciaPriestorová analýza
RodinaRegression modelRegression model
Rok vzniku2010s2002
TvorcaExtension of Rosenbaum & Rubin (1983) IPW to spatial settings; formal treatment by Papadogeorgou et al. (2019)Fotheringham, Brunsdon & Charlton
TypQuasi-experimental / causal inferenceLocal spatial regression
Pôvodný zdrojHirano, K., Imbens, G. W., & Ridder, G. (2003). Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score. Econometrica, 71(4), 1161-1189. DOI ↗Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Ďalšie názvySpatial IPW, Geographic IPW, Spatially-weighted IPW, SIPWGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Príbuzné65
ZhrnutieSpatial Inverse Probability Weighting extends the classical IPW estimator to settings where units are geo-referenced and spatial location is a confounding dimension. By incorporating geographic coordinates or spatial proximity into the propensity score model, it reweights the observed sample so that treatment and control groups are balanced not only on measured covariates but also on spatial structure, enabling credible causal inference from spatially indexed observational data.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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ScholarGatePorovnať metódy: Spatial Inverse Probability Weighting · Geographically Weighted Regression. Získané 2026-06-19 z https://scholargate.app/sk/compare