Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Просторово-часова просторова автокореляція× | Global Moran's I× | |
|---|---|---|
| Галузь | Просторовий аналіз | Просторовий аналіз |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1981–1992 | 1950 |
| Автор методу≠ | Cliff & Ord; extended by Anselin and others | Patrick Alfred Pierce Moran |
| Тип≠ | Spatial autocorrelation statistic | Global spatial autocorrelation test / index |
| Основоположне джерело≠ | Clifford, P., Richardson, S., & Hemon, D. (1989). Assessing the significance of the correlation between two spatial processes. Biometrics, 45(1), 123–134. DOI ↗ | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ |
| Інші назви | STSA, spatiotemporal autocorrelation, space-time Moran's I, temporal spatial dependence | Moran's I, global spatial autocorrelation index, Moran index, GMI |
| Пов'язані≠ | 5 | 6 |
| Підсумок≠ | Space-Time Spatial Autocorrelation extends classic spatial autocorrelation measures — most notably Moran's I — to data that vary across both geographic units and time periods. It detects whether nearby locations that are also temporally close tend to share similar attribute values, revealing clusters, trends, or anomalies that purely spatial or purely temporal analyses would miss. | Global Moran's I is the most widely used single-number summary of spatial autocorrelation across an entire study area. It compares the attribute value at each location with values at neighbouring locations using a spatial weights matrix, and returns a statistic ranging from −1 (perfect dispersion) through 0 (spatial randomness) to +1 (perfect clustering). A significance test determines whether the observed pattern is stronger than random chance. |
| ScholarGateНабір даних ↗ |
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