Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Пространственно-временной индекс Морана (Space-Time Moran's I)× | Локальные индикаторы пространственной ассоциации (LISA)× | |
|---|---|---|
| Область | Пространственный анализ | Пространственный анализ |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1981 | 1995 |
| Автор метода≠ | Cliff & Ord (extended to space-time domain) | Luc Anselin |
| Тип≠ | Spatial autocorrelation statistic | Local spatial statistic |
| Основополагающий источник≠ | Cliff, A. D., & Ord, J. K. (1981). Spatial Processes: Models and Applications. Pion. ISBN: 978-0850860818 | Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| Другие названия | space-time autocorrelation index, ST Moran's I, spatiotemporal Moran's I, space-time I statistic | LISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA |
| Связанные≠ | 5 | 6 |
| Сводка≠ | Space-Time Moran's I extends the classic Moran's I statistic into the spatiotemporal domain, measuring whether observations that are close in both space and time tend to be more similar than those that are distant. It detects clustering, dispersion, or randomness across a combined space-time weight matrix, making it a foundational tool in epidemiology, criminology, and environmental monitoring. | 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. |
| ScholarGateНабор данных ↗ |
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