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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