Salīdzināt metodes
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| Paneļa lokālie telpiskās asociācijas rādītāji (Panel LISA)× | Lokālās telpiskās asociācijas indikatori (LISA)× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1995 (LISA); panel extension 2000s–2010s | 1995 |
| Autors≠ | Anselin (1995), panel extension developed through spatial econometrics literature | Luc Anselin |
| Tips≠ | Local spatial autocorrelation statistic | Local spatial statistic |
| Pirmavots | Anselin, L. (1995). Local indicators of spatial association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ | Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ |
| Citi nosaukumi | Panel LISA, spatiotemporal LISA, panel local spatial autocorrelation, LISA panel extension | LISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA |
| Saistītās≠ | 4 | 6 |
| Kopsavilkums≠ | Panel Local Indicators of Spatial Association extends Anselin's LISA statistics — most commonly Local Moran's I — to panel datasets, identifying spatial clusters and outliers at each location across multiple time periods. By applying local autocorrelation measures repeatedly over time, researchers can detect whether spatial concentration patterns emerge, persist, or dissolve, giving a richer spatiotemporal picture than a single cross-section allows. | 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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