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| Байесовски локални индикатори за пространствена асоциация (Bayesian LISA)× | Локални индикатори за пространствена асоциация (LISA)× | |
|---|---|---|
| Област | Пространствен анализ | Пространствен анализ |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2000s–2010s | 1995 |
| Създател≠ | Extension of Anselin (1995) LISA framework within Bayesian hierarchical modeling traditions (Banerjee, Carlin, Gelfand) | Luc Anselin |
| Тип≠ | Bayesian local spatial statistic | Local spatial statistic |
| Основополагащ източник≠ | 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 ↗ |
| Други названия | Bayesian LISA, Bayesian local spatial autocorrelation, Bayesian local Moran, B-LISA | LISA, local spatial autocorrelation statistics, local Moran's I, Anselin LISA |
| Свързани | 6 | 6 |
| Резюме≠ | Bayesian Local Indicators of Spatial Association extend the classical LISA framework by embedding local spatial association statistics within a Bayesian hierarchical model. Rather than relying on asymptotic permutation-based significance tests, this approach places prior distributions on spatial parameters and derives posterior probabilities that a location is part of a genuine spatial cluster, accounting for uncertainty and borrowing strength across nearby units. | 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. |
| ScholarGateНабор от данни ↗ |
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