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Analiza Gorących Punktów (Getis-Ord Gi*)×Regresja geograficznie ważona (GWR)×
DziedzinaAnaliza przestrzennaAnaliza przestrzenna
RodzinaRegression modelRegression model
Rok powstania19922002
TwórcaArthur Getis and J. Keith OrdFotheringham, Brunsdon & Charlton
TypLocal spatial statisticLocal spatial regression
Źródło pierwotneGetis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206. DOI ↗Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Inne nazwyGetis-Ord Gi* statistic, spatial hot spot detection, cluster and outlier analysis, HSAGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Pokrewne55
PodsumowanieHot Spot Analysis uses the Getis-Ord Gi* local spatial statistic to identify geographic locations where high or low attribute values cluster together to a degree that is statistically significant. Each feature is evaluated in relation to its neighbours, producing a z-score that flags genuine spatial hot spots and cold spots against a background of random variation.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.
ScholarGateZbiór danych
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  3. PUBLISHED
  1. v1
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  3. PUBLISHED

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ScholarGatePorównaj metody: Hot Spot Analysis · Geographically Weighted Regression. Pobrano 2026-06-18 z https://scholargate.app/pl/compare