Salīdzināt metodes
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| Daudzskalu Morana I× | Lokālās telpiskās asociācijas indikatori (LISA)× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1950 (base); multiscale variant 1980s-1990s | 1995 |
| Autors≠ | P. A. P. Moran (base statistic, 1950); multiscale extension developed through spatial ecology and geography literature | Luc Anselin |
| Tips≠ | Spatial autocorrelation statistic | Local spatial statistic |
| Pirmavots≠ | 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 ↗ |
| Citi nosaukumi | multi-scale Moran's I, spatial correlogram Moran, Moran correlogram, multiscale spatial autocorrelation | LISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | Multiscale Moran's I extends the classic global Moran's I statistic by computing spatial autocorrelation across a series of distance lags or spatial scales. The resulting spatial correlogram reveals at which geographic scales clusters or dispersions of a variable exist, offering richer insight than a single summary statistic. | 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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