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Lokálna priestorová regresia×Priestorový model chýb (SEM)×
OdborPriestorová analýzaPriestorová analýza
RodinaRegression modelRegression model
Rok vzniku19961988
TvorcaBrunsdon, Fotheringham & CharltonAnselin
TypSpatially varying coefficient regressionSpatial regression (spatially autocorrelated errors)
Pôvodný zdrojFotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗
Ďalšie názvylocally weighted spatial regression, spatially varying coefficient model, local spatial model, place-based regressionSEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error)
Príbuzné65
ZhrnutieLocal Spatial Regression fits a separate regression model at each location in a study area, allowing regression coefficients to vary continuously across space. Rather than forcing one global slope on all observations, it reveals where and how the relationship between predictors and an outcome changes geographically — producing a map of coefficients rather than a single number.The Spatial Error Model, developed within Anselin's spatial econometrics framework (1988), is a regression model that assumes spatial dependence enters through the error term: the disturbances of neighbouring units are correlated. It is used when unobserved shared factors make the errors of nearby observations move together, and it is estimated by maximum likelihood or GMM rather than ordinary least squares.
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ScholarGatePorovnať metódy: Local Spatial Regression · Spatial Error Model. Získané 2026-06-15 z https://scholargate.app/sk/compare