Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Moran's I telpašās autokorelācijas tests× | Telpiskās nobīdes modelis (SAR / Telpiskais autoregresīvais)× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1950 | 1988 |
| Autors≠ | Patrick A. P. Moran | Anselin (textbook formalisation); LeSage & Pace |
| Tips≠ | Global spatial autocorrelation statistic | Spatial autoregressive regression |
| 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 | SAR model, spatial autoregressive model, spatial lag, Uzamsal Gecikme Modeli (SAR / Spatial Lag) |
| 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 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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