Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Пространствено-времеви коефициент C на Гиъри× | Пространствено-времеви локални индикатори за пространствена асоциация (ST-LISA)× | |
|---|---|---|
| Област | Пространствен анализ | Пространствен анализ |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 1954 / 2010s | 1995 (LISA); space-time extensions developed 2000s–2010s |
| Създател≠ | Geary (1954); extended to space-time by Anselin and others | Extension of Anselin (1995) LISA framework to the space-time domain |
| Тип≠ | Spatial autocorrelation statistic | Local spatial statistic (space-time) |
| Основополагащ източник≠ | Geary, R. C. (1954). The Contiguity Ratio and Statistical Mapping. The Incorporated Statistician, 5(3), 115-145. DOI ↗ | Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| Други названия | ST-Geary's C, spatiotemporal Geary C, space-time contiguity ratio, space-time local spatial autocorrelation | ST-LISA, space-time LISA, spatiotemporal local indicators of spatial association, STLISA |
| Свързани | 6 | 6 |
| Резюме≠ | Space-Time Geary's C extends the classical Geary contiguity ratio to panel or longitudinal spatial data, measuring autocorrelation across both geographic neighbors and adjacent time periods simultaneously. Values below 1 indicate positive space-time clustering; values above 1 indicate dispersion, and a value near 1 suggests random arrangement across the space-time lattice. | Space-Time Local Indicators of Spatial Association (ST-LISA) extend the classic LISA framework of Anselin (1995) into the temporal dimension, identifying locations that exhibit statistically significant spatial clustering or spatial outlier behavior consistently or intermittently across multiple time periods. They decompose global space-time autocorrelation into local contributions, revealing where and when spatial clusters emerge, persist, or dissolve. |
| ScholarGateНабор от данни ↗ |
|
|