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 |
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:
Downloads:
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