Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Laika telpas Geary C× | Telpas-laika Morana I indekss× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1954 / 2010s | 1981 |
| Autors≠ | Geary (1954); extended to space-time by Anselin and others | Cliff & Ord (extended to space-time domain) |
| Tips | Spatial autocorrelation statistic | Spatial autocorrelation statistic |
| Pirmavots≠ | Geary, R. C. (1954). The Contiguity Ratio and Statistical Mapping. The Incorporated Statistician, 5(3), 115-145. DOI ↗ | Cliff, A. D., & Ord, J. K. (1981). Spatial Processes: Models and Applications. Pion. ISBN: 978-0850860818 |
| Citi nosaukumi | ST-Geary's C, spatiotemporal Geary C, space-time contiguity ratio, space-time local spatial autocorrelation | space-time autocorrelation index, ST Moran's I, spatiotemporal Moran's I, space-time I statistic |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | 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 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. |
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