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| Regresja bayesowska odporna (Bayesian Robust Regression)× | Regresja kwantylowa× | |
|---|---|---|
| Dziedzina≠ | Statystyka | Ekonometria |
| Rodzina | Regression model | Regression model |
| Rok powstania≠ | 1993 | 1978 |
| Twórca≠ | Geweke (1993); Gelman et al. (2013) | Koenker & Bassett |
| Typ≠ | Bayesian regression with heavy-tailed errors | Conditional quantile regression |
| Źródło pierwotne≠ | Geweke, J. (1993). Bayesian treatment of the independent Student-t linear model. Journal of Applied Econometrics, 8(S1), S19–S40. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| Inne nazwy≠ | Bayesian heavy-tailed regression, Bayesian Student-t regression, robust Bayesian linear model, BRR | conditional quantile regression, regression quantiles, Kantil Regresyon |
| Pokrewne≠ | 6 | 5 |
| Podsumowanie≠ | Bayesian Robust Regression replaces the Gaussian error assumption of ordinary linear regression with a heavy-tailed distribution — most commonly the Student-t — and estimates all parameters in a Bayesian framework. The heavier tails give outliers less influence on the fitted line, yielding stable coefficient estimates and honest uncertainty intervals even when the data contain unusual observations. | Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails. |
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