Bayesian Estimation for Quantile Regression Mixed Models

Using a Bayesian estimation procedure, this package fits linear quantile regression models such as linear quantile models, linear quantile mixed models, quantile regression joint models for time-to-event and longitudinal data. The estimation procedure is based on the asymmetric Laplace distribution and the 'JAGS' software is used to get posterior samples (Yang, Luo, DeSantis (2019) ).

BeQut

BeQut is a R-package for Bayesian estimation of quantile regression mixed models. Based on the asymmetric Laplace distribution, it also allows to estimate joint models for longitudinal and time-to-event data, linear mixed effects models and simple linear models.

Yang, M., Luo, S., & DeSantis, S. (2019). Bayesian quantile regression joint models: Inference and dynamic predictions. Statistical Methods in Medical Research, 28(8), 2524–2537. https://doi.org/10.1177/0962280218784757

To try the current development version from github, use:

if (!requireNamespace("devtools", quietly = TRUE)) {
    install.packages("devtools")}
devtools::install_github("AntoineBbi/BeQut")

Warning: BeQut package requires JAGS software (http://mcmc-jags.sourceforge.net/).