Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Modèle Bayésien Spatial de Données de Panel× | Modèle de Durbin spatial (SDM)× | |
|---|---|---|
| Domaine | Analyse spatiale | Analyse spatiale |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2009–2014 | 2009 |
| Auteur d'origine≠ | LeSage & Pace; Elhorst | LeSage & Pace |
| Type≠ | Bayesian spatial panel regression | Spatial regression model |
| Source fondatrice≠ | 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 ↗ |
| Alias≠ | Bayesian spatial panel, Bayesian spatial econometrics panel, BSPM, Bayesian panel spatial regression | SDM, spatial mixed model, uzamsal durbin modeli |
| Apparentées | 5 | 5 |
| Résumé≠ | 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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