Võrdle meetodeid
Vaata valitud meetodeid kõrvuti; erinevad read on esile tõstetud.
| Ruumiiline autokorrelatsioon× | Ruumiassotsiatsiooni kohalikud indikaatorid (LISA)× | |
|---|---|---|
| Valdkond | Ruumianalüüs | Ruumianalüüs |
| Perekond | Regression model | Regression model |
| Tekkeaasta≠ | 1950 | 1995 |
| Looja≠ | P. A. P. Moran (global measure, 1950); Roy Geary (Geary's C, 1954); Luc Anselin (LISA, 1995) | Luc Anselin |
| Tüüp≠ | Spatial statistic / exploratory spatial data analysis | Local spatial statistic |
| Algallikas≠ | 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 ↗ |
| Rööpnimetused | spatial dependence, geographic autocorrelation, spatial clustering measure, SA | LISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA |
| Seotud≠ | 5 | 6 |
| Kokkuvõte≠ | Spatial autocorrelation quantifies the degree to which a variable's values at nearby locations resemble each other more (positive autocorrelation) or less (negative autocorrelation) than expected by chance. Global indices such as Moran's I summarise the pattern across the entire study area, while local variants reveal clusters and outliers at the level of individual observations. | LISA, introduced by Luc Anselin in 1995, decomposes a global spatial autocorrelation index into a location-specific statistic for every observation. It identifies where statistically significant spatial clusters and outliers occur on a map, enabling researchers to move beyond a single global summary and pinpoint the geographic sources of spatial dependence. |
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