Quantile Regression for Binary Longitudinal Data

Implements the Bayesian quantile regression model for binary longitudinal data (QBLD) developed in Rahman and Vossmeyer (2019) . The model handles both fixed and random effects and implements both a blocked and an unblocked Gibbs sampler for posterior inference.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


1.0.1 by Ayush Agarwal, a year ago

Browse source code at https://github.com/cran/qbld

Authors: Ayush Agarwal [aut, cre] , Dootika Vats [ctb]

Documentation:   PDF Manual  

GPL-3 license

Imports Rcpp, stats, grDevices, graphics, mcmcse, stableGR, RcppDist, knitr, rmarkdown

Linking to Rcpp, RcppArmadillo, RcppDist

See at CRAN