Description
Bayesian Estimation for Quantile Regression Mixed Models.
Description
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) <doi:10.1177/0962280218784757>).
README.md
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/).