Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| LISA× | Telpiskās nobīdes modelis (SAR / Telpiskais autoregresīvais)× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1995 | 1988 |
| Autors≠ | Luc Anselin | Anselin (textbook formalisation); LeSage & Pace |
| Tips≠ | Local spatial autocorrelation statistic | Spatial autoregressive regression |
| Pirmavots≠ | Anselin, L. (1995). Local Indicators of Spatial Association — LISA. Geographical Analysis, 27(2), 93–115. DOI ↗ | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗ |
| Citi nosaukumi | local Moran's I, local spatial autocorrelation, LISA cluster analysis, LISA — Yerel Uzamsal Otokorelasyon (Local Moran's I) | SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag) |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | LISA, introduced by Luc Anselin in 1995, is a local statistic that computes spatial autocorrelation separately for every observation rather than for the map as a whole. It pinpoints where high or low values cluster and where spatial outliers sit, decomposing the global Moran's I into a contribution from each location. | The Spatial Lag Model is an autoregressive regression that assumes spatial dependence in the dependent variable itself: the outcome values of neighbouring units enter the model as an explanatory term (ρWy). It was formalised in Anselin's Spatial Econometrics (1988) and developed further by LeSage and Pace (2009), and it decomposes spillover effects into direct, indirect, and total impacts. |
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