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Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Kiashirio Imara cha Vyama vya Kimaeneo (Robust LISA)× | Uchambuzi wa Madoa ya Moto ya Getis-Ord Gi* ya Kienyeji× | |
|---|---|---|
| Nyanja | Uchanganuzi wa Kimaeneo | Uchanganuzi wa Kimaeneo |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1995–2000s | 1992–1995 |
| Mwanzilishi≠ | Anselin (LISA, 1995); robust extensions by Assuncao & Reis and subsequent spatial statisticians | Arthur Getis and J. Keith Ord |
| Aina≠ | Local spatial autocorrelation statistic (robust variant) | Local spatial association statistic |
| Chanzo asilia≠ | Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ | Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189–206. DOI ↗ |
| Majina mbadala | Robust LISA, outlier-resistant LISA, robust local spatial autocorrelation, LISA with robust weights | Gi* statistic, Getis-Ord Gi*, local G-star, hot spot statistic |
| Zinazohusiana≠ | 6 | 5 |
| Muhtasari≠ | 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. | The Local Getis-Ord Gi* statistic identifies statistically significant spatial clusters of high values (hot spots) and low values (cold spots) within a study area. Unlike global measures, it produces a z-score for every location, revealing where concentrated clustering occurs and with what statistical confidence. |
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