Porovnat metody
Prohlédněte si vybrané metody vedle sebe; řádky, které se liší, jsou zvýrazněny.
| Robustní bayesovské průměrování modelů× | Bayesovská regrese× | |
|---|---|---|
| Obor | Bayesovská statistika | Bayesovská statistika |
| Rodina | Bayesian methods | Bayesian methods |
| Rok vzniku≠ | 1999–2012 | — |
| Tvůrce≠ | Hoeting, Madigan, Raftery, Volinsky (BMA); robustness extensions by Ley & Steel and others | — |
| Typ≠ | Bayesian model selection and averaging | Bayesian linear model |
| Původní zdroj≠ | Hoeting, J. A., Madigan, D., Raftery, A. E., & Volinsky, C. T. (1999). Bayesian model averaging: A tutorial. Statistical Science, 14(4), 382–401. link ↗ | 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 |
| Další názvy≠ | robust BMA, outlier-robust BMA, robust model averaging, heavy-tailed BMA | bayesian linear regression, probabilistic regression, bayesian regresyon |
| Příbuzné≠ | 6 | 2 |
| Shrnutí≠ | Robust Bayesian model averaging extends standard BMA by replacing sensitive conjugate priors with heavy-tailed or mixture priors (e.g., mixtures of g-priors), and optionally robust likelihoods, so that posterior model probabilities and averaged estimates remain stable when data contain outliers, influential observations, or when the prior on model parameters would otherwise dominate the results. | 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. |
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