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 |
Documentation:
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