Fits Bayesian mixed-effects (multilevel) quantile regression models using the
asymmetric Laplace working likelihood and Stan, with an lme4-style formula
interface, one or several quantiles per call, optional LKJ-correlated random
effects, post-hoc non-crossing rearrangement, and the Yang, Wang and He
(2016) posterior-variance correction for valid fixed-effect inference.
References
Yu, K. and Moyeed, R. A. (2001). Bayesian quantile regression. Statistics & Probability Letters, 54(3), 437-447.
Geraci, M. and Bottai, M. (2014). Linear quantile mixed models. Statistics and Computing, 24(3), 461-479.
Yang, Y., Wang, H. J. and He, X. (2016). Posterior inference in Bayesian quantile regression with asymmetric Laplace likelihood. International Statistical Review, 84(3), 327-344.
Author
Maintainer: Kailas Venkitasubramanian kailasv@gmail.com [copyright holder]