Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Indicele I al lui Moran× | Indicator Moran I Local (LISA)× | |
|---|---|---|
| Domeniu | Analiză spațială | Analiză spațială |
| Familie | Regression model | Regression model |
| Anul apariției≠ | 1950 | 1995 |
| Autorul original≠ | Patrick A. P. Moran | Luc Anselin |
| Tip≠ | Spatial autocorrelation statistic | Local spatial autocorrelation statistic |
| Sursa seminală≠ | Moran, P. A. P. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ | Anselin, L. (1995). Local indicators of spatial association—LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| Denumiri alternative | Moran's I statistic, global Moran's I, spatial autocorrelation index, Moran index | Local Indicator of Spatial Association, LISA statistic, Anselin Local Moran, local spatial autocorrelation index |
| Înrudite | 6 | 6 |
| Rezumat≠ | Moran's I is the standard global statistic for detecting spatial autocorrelation: whether nearby locations tend to share similar values. The index ranges from approximately −1 (perfect dispersion) through 0 (spatial randomness) to +1 (perfect clustering), allowing researchers to test whether a geographic pattern differs from complete spatial randomness with a single, interpretable number. | 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. |
| ScholarGateSet de date ↗ |
|
|