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:

Reference manual:	qbld.pdf
Vignettes:	Using qbld

Downloads:

Package source:	qbld_1.0.3.tar.gz
Windows binaries:	r-prerel: qbld_1.0.3.zip, r-release: qbld_1.0.3.zip, r-oldrel: qbld_1.0.3.zip
macOS binaries:	r-prerel (arm64): qbld_1.0.3.tgz, r-release (arm64): qbld_1.0.3.tgz, r-oldrel (arm64): qbld_1.0.3.tgz, r-prerel (x86_64): qbld_1.0.3.tgz, r-release (x86_64): qbld_1.0.3.tgz
Old sources:	qbld archive

Linking:

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