方法对比
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| 贝叶斯面板数据分析× | 贝叶斯随机效应模型× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1971–1999 | 1972–1995 |
| 提出者≠ | Zellner (1971); Hsiao, Pesaran, and Tahmiscioglu (1999) | Lindley & Smith (1972); extended by Gelman, Rubin and colleagues |
| 类型≠ | Bayesian estimation for panel data | Bayesian hierarchical panel model |
| 开创性文献≠ | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 | Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955 |
| 别名 | Bayesian panel model, Bayesian longitudinal model, hierarchical panel model, Bayesian multilevel panel | Bayesian hierarchical model, Bayesian mixed effects model, Bayesian multilevel model, BREM |
| 相关 | 5 | 5 |
| 摘要≠ | Bayesian panel data analysis applies Bayesian inference to models with repeated observations on multiple units. By placing prior distributions on coefficients and variance components, it merges prior knowledge with the observed panel likelihood to produce full posterior distributions for fixed or random effects, slope heterogeneity, and variance parameters — rather than point estimates and asymptotic standard errors. | The Bayesian random effects model combines panel-data random effects with a Bayesian prior framework, allowing unit-specific effects to be treated as draws from a population distribution whose hyperparameters are estimated from the data. This produces regularised, uncertainty-quantified estimates that borrow strength across units — particularly valuable for short panels, sparse groups, or settings where frequentist variance-component estimation is unstable. |
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