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분야통계학계량경제학
계열Regression modelRegression model
기원 연도19931978
창시자Geweke (1993); Gelman et al. (2013)Koenker & Bassett
유형Bayesian regression with heavy-tailed errorsConditional quantile regression
원전Geweke, 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 ↗
별칭Bayesian heavy-tailed regression, Bayesian Student-t regression, robust Bayesian linear model, BRRconditional quantile regression, regression quantiles, Kantil Regresyon
관련65
요약Bayesian 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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ScholarGate방법 비교: Bayesian Robust Regression · Quantile Regression. 2026-06-15에 다음에서 검색함: https://scholargate.app/ko/compare