qbld: Quantile Regression for Binary Longitudinal Data
Implements the Bayesian quantile regression model for binary longitudinal data 
             (QBLD) developed in Rahman and Vossmeyer (2019) <doi:10.1108/S0731-90532019000040B009>.
             The model handles both fixed and random effects and implements both a blocked
             and an unblocked Gibbs sampler for posterior inference.
| Version: | 1.0.3 | 
| Depends: | R (≥ 3.5) | 
| Imports: | Rcpp, stats, grDevices, graphics, mcmcse, stableGR, RcppDist, knitr, rmarkdown | 
| LinkingTo: | Rcpp, RcppArmadillo, RcppDist | 
| Published: | 2022-01-06 | 
| DOI: | 10.32614/CRAN.package.qbld | 
| Author: | Ayush Agarwal [aut, cre], Dootika Vats [ctb] | 
| Maintainer: | Ayush Agarwal <ayush.agarwal50 at gmail.com> | 
| License: | GPL-3 | 
| NeedsCompilation: | yes | 
| Citation: | qbld citation info | 
| CRAN checks: | qbld results | 
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