方法对比
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| 贝叶斯空间面板模型× | 空间杜宾模型 (SDM)× | |
|---|---|---|
| 领域 | 空间分析 | 空间分析 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2009–2014 | 2009 |
| 提出者≠ | LeSage & Pace; Elhorst | LeSage & Pace |
| 类型≠ | Bayesian spatial panel regression | Spatial regression model |
| 开创性文献≠ | 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 ↗ |
| 别名≠ | Bayesian spatial panel, Bayesian spatial econometrics panel, BSPM, Bayesian panel spatial regression | SDM, spatial mixed model, uzamsal durbin modeli |
| 相关 | 5 | 5 |
| 摘要≠ | 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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