Bayesian quantile regression

By Keming Yu, Rana Moyeed. 2001

463 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/a5a6fb8aabe8a4721afa1870a207267ea3f93c15

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In Statistics and Probability

Citations in the corpus

Bayesian quantile regression for count data with application to environmental epidemiology (2010, methodology): “Various extensions to this have since been proposed, including a Bayesian implementation (Yu and Moyeed, 2001) and incorporating correlated responses within a longitudinal study (Geraci and Bottai, 2007).”
Generalized Additive Models for Exceedances of High Thresholds With an Application to Return Level Estimation for U.S. Wind Gusts (2019, methodology): “…inference is enabled by analogy between the tilted loss function typically used in quantile regression and the asymmetric Laplace distribution (Yu and Moyeed 2001), so that Y(s, t) | u(s, t), σ(s, t) ∼ ALD(u(s, t), σ(s, t)) (4) with density function f ( y; u(s, t), σ ) = τ(1 − τ) σ (s, t) exp…”
Bayesian structured additive distributional regression with an application to regional income inequality in Germany (2015, background): “…indexed by a prespecified asymmetry parameter (the quantile or expectile level); see Koenker and Bassett (1978), Newey and Powell (1987) for the original references and Koenker (2005), Schnabel and Eilers (2009), Sobotka and Kneib (2012), Yu and Moyeed (2001) for more recent overviews.”
Statistical downscaling of precipitation using quantile regression (2013, background): “Yu and Moyeed (2001) proposed the use of a pseudo-likelihood function of the form:”
Calibrating general posterior credible regions (2015, methodology): “A workaround that has been considered by several authors (e.g., Sriram 2015; Sriram et al. 2013; Yu and Moyeed 2001) is to use a (misspecified) asymmetric Laplace likelihood.”
Posterior Consistency of Bayesian Quantile Regression Based on the Misspecified Asymmetric Laplace Density (2013, unknown): “Yu and Moyeed (2001) proposed the idea of Bayesian quantile regression by assuming ALD for the response.”
Bayesian Nonstationary Frequency Analysis of Hydrological Variables 1 (2011, methodology): “Further development of the local likelihood model JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION 503 JAWRA (Sankarasubramanian and Lall, 2003) and the Bayesian quantile regression method (Yu and Moyeed, 2001 for instance) deserves also much attention.”
Fast Calibrated Additive Quantile Regression (2017, methodology): “To circumvent this problem, Yu and Moyeed (2001) propose adopting an asymmetric Laplace (AL) model for p(y|x), due to the equivalence between the AL negative logdensity and the pinball loss.”
A partially collapsed Gibbs sampler for Bayesian quantile regression (2009, methodology): “A few of the difierent models and sampling algorithms for Bayesian quantile regression include MCMC (Markov chain Monte Carlo) or RJMCMC (Reversible Jump Markov Chain Monte Carlo) methods via an asymmetric Laplace distribution for the likelihood function ( Yu and Moyeed, 2001; Yu and Stander, 2007;”
Bayesian Semiparametric Modelling in Quantile Regression (2009, methodology): “As in Yu & Moyeed (2001), we use a quadratic quantile regression model 0 + 1x + 2x2, where x denotes age in years.”