方法对比

	贝叶斯稳健回归	分位数回归
领域	统计学	计量经济学
方法族	Regression model	Regression model
起源年份	1993	1978
提出者	Geweke (1993); Gelman et al. (2013)	Koenker & Bassett
类型	Bayesian regression with heavy-tailed errors	Conditional quantile regression
开创性文献	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.
别名	Bayesian heavy-tailed regression, Bayesian Student-t regression, robust Bayesian linear model, BRR	conditional quantile regression, regression quantiles, Kantil Regresyon
相关	6	5
摘要	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.