exdqlm - Extended Dynamic Quantile Linear Models

Bayesian quantile-regression routines for dynamic state-space models and static regression under the extended asymmetric Laplace (exAL) error distribution. The dynamic state-space models are extended dynamic quantile linear models (exDQLMs). The package combines dynamic exDQLM inference via LDVB, MCMC, and legacy ISVB with static exAL regression via LDVB and MCMC, reduced AL/DQLM paths through fixed skewness, component builders for trend/seasonality/regression blocks, static shrinkage priors including ridge, regularized horseshoe, and 'rhs_ns', evidence lower bound diagnostics, optional C++ accelerators, and posterior predictive synthesis across separately fitted quantiles through 'quantileSynthesis()'. Dynamic exDQLM methods are described in Barata et al. (2020) <doi:10.1214/21-AOAS1497>.