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Robustais Morana I×Robustie lokālie telpiskās asociācijas rādītāji (Robust LISA)×
NozareTelpiskā analīzeTelpiskā analīze
SaimeRegression modelRegression model
Izcelsmes gads1990s–2000s1995–2000s
AutorsExtension of Moran (1950); robust adaptations developed in spatial statistics literatureAnselin (LISA, 1995); robust extensions by Assuncao & Reis and subsequent spatial statisticians
TipsRobust spatial autocorrelation statisticLocal spatial autocorrelation statistic (robust variant)
PirmavotsAnselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗
Citi nosaukumioutlier-resistant Moran's I, robust spatial autocorrelation test, median-based Moran statistic, robust global spatial associationRobust LISA, outlier-resistant LISA, robust local spatial autocorrelation, LISA with robust weights
Saistītās66
KopsavilkumsRobust Moran's I is an outlier-resistant adaptation of the classic Moran's I spatial autocorrelation statistic. By replacing the standard mean-based standardization with resistant measures of center and spread, it detects genuine geographic clustering without being distorted by a small number of extreme values in the attribute of interest.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.
ScholarGateDatu kopa
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  1. v1
  2. 2 Avoti
  3. PUBLISHED

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ScholarGateSalīdzināt metodes: Robust Moran's I · Robust Local Indicators of Spatial Association. Izgūts 2026-06-19 no https://scholargate.app/lv/compare