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| Байесов регресионен модел× | Мултиномиална логистична регресия× | |
|---|---|---|
| Област≠ | Бейсови методи | Иконометрия |
| Семейство≠ | Bayesian methods | Regression model |
| Година на възникване≠ | — | 1974 |
| Създател≠ | — | McFadden |
| Тип≠ | Bayesian linear model | Multinomial logistic regression |
| Основополагащ източник≠ | 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 |
| Други названия≠ | bayesian linear regression, probabilistic regression, bayesian regresyon | multinomial logistic regression, polytomous logistic regression, softmax regression, Çok Kategorili Lojistik Regresyon |
| Свързани≠ | 2 | 5 |
| Резюме≠ | 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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