Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Локальные индикаторы пространственной ассоциации (LISA)× | 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 | LISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA | spatial dependence, geographic autocorrelation, spatial clustering measure, SA |
| Связанные≠ | 6 | 5 |
| Сводка≠ | LISA, introduced by Luc Anselin in 1995, decomposes a global spatial autocorrelation index into a location-specific statistic for every observation. It identifies where statistically significant spatial clusters and outliers occur on a map, enabling researchers to move beyond a single global summary and pinpoint the geographic sources of spatial dependence. | 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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