Сравнение методов

	Байесовская робастная регрессия	Квантильная регрессия
Область	Статистика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1993	1978
Автор метода	Geweke (1993); Gelman et al. (2013)	Koenker & Bassett
Тип	Bayesian regression with heavy-tailed errors	Conditional quantile regression
Основополагающий источник	Geweke, J. (1993). Bayesian treatment of the independent Student-t linear model. Journal of Applied Econometrics, 8(S1), S19–S40.	Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50.
Другие названия	Bayesian heavy-tailed regression, Bayesian Student-t regression, robust Bayesian linear model, BRR	conditional quantile regression, regression quantiles, Kantil Regresyon
Связанные	6	5
Сводка	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.