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강건한 Getis-Ord Gi* 통계량×Robust Local Indicators of Spatial Association (Robust LISA)×
분야공간분석공간분석
계열Regression modelRegression model
기원 연도1992 (base); robust variants circa 2000s–2010s1995–2000s
창시자Getis & Ord (base statistic); robust extensions developed in subsequent spatial statistics literatureAnselin (LISA, 1995); robust extensions by Assuncao & Reis and subsequent spatial statisticians
유형Local spatial statisticLocal spatial autocorrelation statistic (robust variant)
원전Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189–206. DOI ↗Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗
별칭Robust Gi*, Robust local Gi star, outlier-resistant hot spot analysis, robust local spatial autocorrelation Gi*Robust LISA, outlier-resistant LISA, robust local spatial autocorrelation, LISA with robust weights
관련56
요약The Robust Getis-Ord Gi* statistic extends the classical Gi* hot-spot measure to handle outliers in spatial data. By using robust estimators of the mean and variance — such as trimmed means, medians, or down-weighted influential observations — it identifies statistically significant spatial clusters of high or low values even when the attribute distribution contains extreme values that would distort the standard Gi*.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.
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