方法对比
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| 贝叶斯 Tobit 模型× | Tobit删失回归模型× | |
|---|---|---|
| 领域≠ | 统计学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1958 (classical); 1992 (Bayesian formulation) | 1958 |
| 提出者≠ | James Tobin (classical Tobit, 1958); Siddhartha Chib (Bayesian Tobit, 1992) | James Tobin |
| 类型≠ | Bayesian censored/limited-dependent-variable regression | Censored regression (limited dependent variable) |
| 开创性文献≠ | Tobin, J. (1958). Estimation of relationships for limited dependent variables. Econometrica, 26(1), 24–36. DOI ↗ | Tobin, J. (1958). Estimation of Relationships for Limited Dependent Variables. Econometrica, 26(1), 24-36. DOI ↗ |
| 别名≠ | Bayesian censored regression, Bayesian Type I Tobit, Bayesian truncated regression, Tobit with priors | censored regression, limited dependent variable model, Tobit Modeli (Sansürlü Regresyon) |
| 相关≠ | 5 | 4 |
| 摘要≠ | The Bayesian Tobit model extends Tobin's censored regression framework by replacing maximum-likelihood point estimates with a full posterior distribution over regression coefficients and error variance. By embedding Gibbs sampling with data augmentation, it produces credible intervals, handles small censored samples gracefully, and naturally incorporates prior knowledge about effect sizes. | The Tobit model is a regression for outcomes that are censored at a threshold, estimating the relationship by maximum likelihood. Introduced by James Tobin in 1958, it addresses the pile-up of observations at a limit (typically zero) in data such as spending, wages, or duration. |
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