Package: AGBQR
Type: Package
Title: Adaptive Generalized Bayesian Quantile Regression
Version: 0.1.0
Date: 2026-06-16
Authors@R: person(given = "Khder",
                  family = "Alakkari",
                  email = "khderalakkari1990@gmail.com",
                  role = c("aut", "cre"))
Description: Implements adaptive generalized Bayesian quantile regression with quantile-specific learning rates, HAC-based calibration, Gibbs posterior simulation, posterior summaries, predictive evaluation, and visualization tools. The package builds on the generalized Bayesian composite quantile regression framework of Hardy and Korobilis (2026) <doi:10.2139/ssrn.6618603> by allowing learning rates to vary across quantile levels. The implementation is designed for empirical work with small and moderate time-series samples where posterior calibration and tail-specific inference are important.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: quantreg, MASS, stats
Suggests: testthat
NeedsCompilation: no
Packaged: 2026-06-16 14:02:46 UTC; khder
Author: Khder Alakkari [aut, cre]
Maintainer: Khder Alakkari <khderalakkari1990@gmail.com>
Repository: CRAN
Date/Publication: 2026-06-22 15:00:38 UTC
