Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Moran's I telpašās autokorelācijas tests× | Telpiskais kļūdu modelis (SEM)× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1950 | 1988 |
| Autors≠ | Patrick A. P. Moran | Anselin |
| Tips≠ | Global spatial autocorrelation statistic | Spatial regression (spatially autocorrelated errors) |
| Pirmavots≠ | Moran, P.A.P. (1950). Notes on Continuous Stochastic Phenomena. Biometrika, 37(1/2), 17–23. DOI ↗ | Anselin, L. (1988). Spatial Econometrics: Methods and Models. Kluwer Academic. DOI ↗ |
| Citi nosaukumi≠ | global Moran's I, spatial autocorrelation test, Moran's I Uzamsal Otokorelasyon Testi | SEM, spatial error regression, spatial autoregressive error model, Uzamsal Hata Modeli (SEM / Spatial Error) |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | Moran's I is a global statistic, introduced by Patrick Moran in 1950, that measures whether and how a continuous variable is spatially autocorrelated across mapped units. A positive value signals clustering of similar values, a negative value signals a dispersed (checkerboard) pattern, and it is most often used as a diagnostic before moving to spatial regression. | 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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