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: | 1.0.1 |
| Depends: | R (≥ 3.5) |
| Imports: | Rcpp, stats, grDevices, graphics, mcmcse, stableGR, RcppDist, knitr, rmarkdown |
| LinkingTo: | Rcpp, RcppArmadillo, RcppDist |
| Published: | 2020-09-11 |
| 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 |
| Reference manual: | qbld.pdf |
| Vignettes: |
Using qbld |
| Package source: | qbld_1.0.1.tar.gz |
| Windows binaries: | r-devel: qbld_1.0.1.zip, r-release: qbld_1.0.1.zip, r-oldrel: qbld_1.0.1.zip |
| macOS binaries: | r-release: qbld_1.0.1.tgz, r-oldrel: qbld_1.0.1.tgz |
| Old sources: | qbld archive |
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