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| Bayesian Regression× | 多项逻辑回归× | |
|---|---|---|
| 领域≠ | 贝叶斯 | 计量经济学 |
| 方法族≠ | Bayesian methods | Regression model |
| 起源年份≠ | — | 1974 |
| 提出者≠ | — | McFadden |
| 类型≠ | Bayesian linear model | Multinomial logistic regression |
| 开创性文献≠ | 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 | McFadden, D. (1974). Conditional Logit Analysis of Qualitative Choice Behavior. In P. Zarembka (Ed.), Frontiers in Econometrics (pp. 105-142). Academic Press. ISBN: 978-0127761503 |
| 别名≠ | bayesian linear regression, probabilistic regression, bayesian regresyon | multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon |
| 相关≠ | 2 | 5 |
| 摘要≠ | Bayesian regression is a probabilistic version of linear regression that treats the model parameters as uncertain quantities. Instead of returning a single best-fit estimate, it combines prior knowledge with the observed data to produce a full posterior probability distribution for each parameter, from which credible intervals and predictions are read off. | Multinomial logistic regression is a maximum-likelihood method for a nominal (unordered) dependent variable with more than two categories. Building on McFadden's 1974 treatment of qualitative choice, it gives each category its own set of coefficients relative to a reference category. |
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