CRAN
Abstract
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. Project supported by Google summer of code.
Type
Publication
In The Comprehensive R Archive Network
Ayush Agarwal
Statistics | Finance | Psychology | Music | Cars | Photography
My research interests include Markov Chains, Bayesian Statistics and Time series.