Bayesian quantile regression for longitudinal data models

By Youxi Luo, Heng Lian, Maozai Tian. 2012

69 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/430d75e569a8a687813f7216007ec6ce6444fa8f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Huixia Judy Wang
2. Yunwen Yang
3. Xuming He
4. Ryan Martin
5. Nicholas Syring

In Statistics and Probability

1. Huixia Judy Wang
2. Yunwen Yang
3. Xuming He
4. Ying Wei
5. Damian W. Betebenner
6. Lan Wang
7. Antonio F. Galvao
8. Victor Chernozhukov

Citations in the corpus

• Posterior Inference in Bayesian Quantile Regression with Asymmetric Laplace Likelihood (2016, methodology): “In recent years, the AL likelihood has been adopted for Bayesian quantile regression in different contexts and applications, for instance, quantile regression with random effects (Geraci & Bottai, 2007; Yuan & Yin, 2009; Geraci & Bottai, 2013; Yue & Rue, 2011; Luo et al., 2014; Wang, 2012), variable”