Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Telpiskās regresijas laika un telpas analīze× | Telpiskais Durbina modelis (SDM)× | |
|---|---|---|
| Nozare | Telpiskā analīze | Telpiskā analīze |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1990s–2000s | 2009 |
| Autors≠ | Anselin, LeSage, Pace and colleagues in spatial econometrics | LeSage & Pace |
| Tips≠ | Spatio-temporal regression model | Spatial regression model |
| Pirmavots≠ | LeSage, J. P., & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press / Taylor & Francis. ISBN: 978-1420064247 | LeSage, J. & Pace, R. K. (2009). Introduction to Spatial Econometrics. CRC Press. DOI ↗ |
| Citi nosaukumi≠ | spatio-temporal regression, spatial panel regression, space-time regression, ST spatial regression | SDM, spatial mixed model, uzamsal durbin modeli |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | Space-Time Spatial Regression extends classical spatial regression to panel settings where georeferenced units are observed across multiple time periods. By embedding a spatial weights matrix into a panel regression framework, it simultaneously controls for spatial dependence among cross-sectional units and temporal dynamics, yielding unbiased and consistent estimates in spatio-temporal data. | The Spatial Durbin Model is a general spatial regression model that includes a spatial lag of both the dependent variable (ρWy) and the explanatory variables (WXθ). Introduced as the recommended starting point by LeSage and Pace (2009), it nests the spatial autoregressive (SAR) and spatial error (SEM) models as special cases. |
| ScholarGateDatu kopa ↗ |
|
|