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Robustne C Geary’ego×Solidne lokalne wskaźniki stowarzyszenia przestrzennego (Robust LISA)×
DziedzinaAnaliza przestrzennaAnaliza przestrzenna
RodzinaRegression modelRegression model
Rok powstania1954 (base); robust variants: 1990s–2000s1995–2000s
TwórcaGeary (1954); robust extensions by Anselin and spatial statisticiansAnselin (LISA, 1995); robust extensions by Assuncao & Reis and subsequent spatial statisticians
TypRobust spatial autocorrelation statisticLocal spatial autocorrelation statistic (robust variant)
Źródło pierwotneGeary, R. C. (1954). The contiguity ratio and statistical mapping. The Incorporated Statistician, 5(3), 115–145. DOI ↗Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗
Inne nazwyrobust Geary contiguity ratio, outlier-resistant Geary's C, robust spatial contiguity statistic, robust Geary CRobust LISA, outlier-resistant LISA, robust local spatial autocorrelation, LISA with robust weights
Pokrewne66
PodsumowanieRobust Geary's C adapts the classical Geary contiguity ratio — a measure of spatial autocorrelation based on pairwise squared differences between neighbouring locations — to resist distortion by spatial outliers and influential observations. It retains the local sensitivity of Geary's C while producing more reliable inferences when the spatial data contain extreme values or non-normal distributions.Robust Local Indicators of Spatial Association extend Anselin's LISA framework to handle outliers, extreme values, and spatially heterogeneous populations. By applying outlier-resistant adjustments to the spatial weights or the standardised values, Robust LISA identifies statistically significant local clusters and spatial outliers without the distortions caused by highly influential observations.
ScholarGateZbiór danych
  1. v1
  2. 2 Źródła
  3. PUBLISHED
  1. v1
  2. 2 Źródła
  3. PUBLISHED

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ScholarGatePorównaj metody: Robust Geary's C · Robust Local Indicators of Spatial Association. Pobrano 2026-06-19 z https://scholargate.app/pl/compare