Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Пространственно-временной индекс Морана (Space-Time Moran's I)× | Локальный индекс пространственной автокорреляции (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 autocorrelation 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 | Local Indicator of Spatial Association, LISA statistic, Anselin Local Moran, local spatial autocorrelation index |
| 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. | Local Moran's I, introduced by Luc Anselin in 1995, is a Local Indicator of Spatial Association (LISA) that decomposes global spatial autocorrelation into location-specific contributions. For every observation it produces a signed statistic and a significance value, enabling researchers to identify spatial clusters (high-high, low-low) and spatial outliers (high-low, low-high) on a map. |
| ScholarGateНабор данных ↗ |
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