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| Bayesowski przestrzenny model panelowy× | Model przestrzenny Durbina (SDM)× | |
|---|---|---|
| Dziedzina | Analiza przestrzenna | Analiza przestrzenna |
| Rodzina | Regression model | Regression model |
| Rok powstania≠ | 2009–2014 | 2009 |
| Twórca≠ | LeSage & Pace; Elhorst | LeSage & Pace |
| Typ≠ | Bayesian spatial panel regression | Spatial regression model |
| Źródło pierwotne≠ | 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 ↗ |
| Inne nazwy≠ | Bayesian spatial panel, Bayesian spatial econometrics panel, BSPM, Bayesian panel spatial regression | SDM, spatial mixed model, uzamsal durbin modeli |
| Pokrewne | 5 | 5 |
| Podsumowanie≠ | The Bayesian Spatial Panel Model estimates spatial interaction effects (spatial lag, spatial error, or Durbin) in panel data using Bayesian inference via Markov Chain Monte Carlo (MCMC). It combines the ability to control for unobserved unit- and time-specific heterogeneity with principled uncertainty quantification, making it suitable for georeferenced longitudinal datasets in economics, public health, and regional science. | 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. |
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