summary.exalStaticMCMC

Summary Method for <code>exalStaticMCMC</code> Objects

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>.

Raquel Barata

exdqlm

Extended Dynamic Quantile Linear Models

Raquel Prado

Bruno Sanso

Antonio Aguirre

summary.exalStaticMCMC function

<dl><dt>object</dt>
<dd>An <code>exalStaticMCMC</code> object.</dd>
<dt>...</dt>
<dd>Additional arguments (unused).</dd></dl>

Arguments

Summary Method for exalStaticMCMC Objects — summary.exalStaticMCMC

<dl>

<dt>object</dt>
<dd>An <code>exalStaticMCMC</code> object.</dd>


<dt>...</dt>
<dd>Additional arguments (unused).</dd>

</dl>

summary.exalStaticMCMC: Summary Method for `exalStaticMCMC` Objects

Description

Usage

Arguments