Krahasoni metodat

	Regresioni Kuantil Bayesian	Regresioni Robust i Kuantileve
Fusha	Statistikë	Statistikë
Familja	Regression model	Regression model
Viti i origjinës	2001–2011	1993–1997
Krijuesi	Kozumi & Kobayashi; building on Yu & Moyeed (2001)	Koenker & Bassett (1978); robust extensions by Machado (1993) and He (1997)
Lloji	Bayesian semiparametric regression	Robust semiparametric regression
Burimi themelues	Kozumi, H., & Kobayashi, G. (2011). Gibbs sampling methods for Bayesian quantile regression. Journal of Statistical Computation and Simulation, 81(11), 1565–1578.	Koenker, R. (2005). Quantile Regression. Cambridge University Press. ISBN: 978-0521608275
Emërtime të tjera	BQR, Bayesian quantile regression model, asymmetric Laplace Bayesian regression, posterior quantile regression	robust QR, outlier-resistant quantile regression, bounded-influence quantile regression, RQR
Të lidhura	6	6
Përmbledhja	Bayesian Quantile Regression estimates the full posterior distribution of regression coefficients at any chosen quantile of the outcome. By combining the asymmetric Laplace likelihood with prior distributions over the coefficients, it delivers uncertainty-quantified estimates of conditional quantiles — such as the median, the 10th, or the 90th percentile — without assuming Gaussian errors.	Robust Quantile Regression estimates conditional quantiles of a response variable while simultaneously downweighting the influence of outliers. By combining the asymmetric loss function of standard quantile regression with bounded-influence or M-estimation weights, it provides reliable quantile estimates even when data contain extreme observations or heavy-tailed error distributions.