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| 강건 모란 I (Robust Moran's I)× | Robust Local Indicators of Spatial Association (Robust LISA)× | |
|---|---|---|
| 분야 | 공간분석 | 공간분석 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1990s–2000s | 1995–2000s |
| 창시자≠ | Extension of Moran (1950); robust adaptations developed in spatial statistics literature | Anselin (LISA, 1995); robust extensions by Assuncao & Reis and subsequent spatial statisticians |
| 유형≠ | Robust spatial autocorrelation statistic | Local spatial autocorrelation statistic (robust variant) |
| 원전 | Anselin, 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 ↗ |
| 별칭 | outlier-resistant Moran's I, robust spatial autocorrelation test, median-based Moran statistic, robust global spatial association | Robust LISA, outlier-resistant LISA, robust local spatial autocorrelation, LISA with robust weights |
| 관련 | 6 | 6 |
| 요약≠ | Robust 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. |
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