Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Локальный коэффициент Geary's C× | Пространственная автокорреляция× | |
|---|---|---|
| Область | Пространственный анализ | Пространственный анализ |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1995 | 1950 |
| Автор метода≠ | Luc Anselin | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) |
| Тип≠ | Local spatial statistic | Spatial statistic / exploratory spatial data analysis |
| Основополагающий источник≠ | Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| Другие названия | Local Geary, local spatial contiguity ratio, LISA Geary, local c statistic | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| Связанные≠ | 6 | 5 |
| Сводка≠ | Local Geary's C is a local indicator of spatial association (LISA) that measures, for each location, how dissimilar its value is from its immediate neighbours. Unlike Local Moran's I, which detects clustering of similar values, Local Geary's C focuses on squared value differences and is especially sensitive to local spatial outliers and local heterogeneity. | Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations. |
| ScholarGateНабор данных ↗ |
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