Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Analyse globale des points chauds (Statistique G de Getis-Ord)× | Analyse des points chauds (Getis-Ord Gi*)× | |
|---|---|---|
| Domaine | Analyse spatiale | Analyse spatiale |
| Famille | Regression model | Regression model |
| Année d'origine | 1992 | 1992 |
| Auteur d'origine | Arthur Getis and J. Keith Ord | Arthur Getis and J. Keith Ord |
| Type≠ | Global spatial concentration test | Local spatial statistic |
| Source fondatrice | Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206. DOI ↗ | Getis, A., & Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3), 189-206. DOI ↗ |
| Alias | Global G statistic, Getis-Ord G, global spatial clustering test, global concentration statistic | Getis-Ord Gi* statistic, spatial hot spot detection, cluster and outlier analysis, HSA |
| Apparentées | 5 | 5 |
| Résumé≠ | Global Hot Spot Analysis uses the Getis-Ord G statistic to determine whether high or low attribute values are spatially concentrated across an entire study area. It answers one question: is there overall clustering of high values (a hot spot tendency) or low values (a cold spot tendency) in the dataset as a whole, producing a single summary test for the full region. | Hot Spot Analysis uses the Getis-Ord Gi* local spatial statistic to identify geographic locations where high or low attribute values cluster together to a degree that is statistically significant. Each feature is evaluated in relation to its neighbours, producing a z-score that flags genuine spatial hot spots and cold spots against a background of random variation. |
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