Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| LISA× | Telpiskais kļūdu modelis (SEM)× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1995 | 1988 |
| Autors≠ | Luc Anselin | Anselin |
| Tips≠ | Local spatial autocorrelation statistic | Spatial regression (spatially autocorrelated errors) |
| 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) | SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error) |
| 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 Error Model, developed within Anselin's spatial econometrics framework (1988), is a regression model that assumes spatial dependence enters through the error term: the disturbances of neighbouring units are correlated. It is used when unobserved shared factors make the errors of nearby observations move together, and it is estimated by maximum likelihood or GMM rather than ordinary least squares. |
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