Compute highest density intervals for parameters based on simulated
posterior draws from a <code>qbrms_fit</code>.

Provides a 'brms'-like interface for fitting Bayesian regression models
using 'INLA' (Integrated Nested Laplace Approximations) and 'TMB' (Template Model Builder).
The package offers faster model fitting while maintaining familiar 'brms' syntax and
output formats. Supports fixed and mixed effects models, multiple probability distributions,
conditional effects plots, and posterior predictive checks with summary methods compatible
with 'brms'. 'TMB' integration provides fast ordinal regression capabilities. Implements
methods adapted from 'emmeans' for marginal means estimation and 'bayestestR' for Bayesian
inference assessment. Methods are based on Rue et al. (2009) <doi:10.1111/j.1467-9868.2008.00700.x>,
Kristensen et al. (2016) <doi:10.18637/jss.v070.i05>, Lenth (2016) <doi:10.18637/jss.v069.i01>,
Bürkner (2017) <doi:10.18637/jss.v080.i01>, Makowski et al. (2019) <doi:10.21105/joss.01541>,
and Kruschke (2014, ISBN:9780124058880).

Tony Myers

qbrms

Quick Bayesian Regression Models Using 'INLA' with 'brms' Syntax

hdi function

<dl><dt>object</dt>
<dd>A <code>qbrms_fit</code>.</dd>
<dt>parameters</dt>
<dd>Optional character vector; default uses all fixed effects.</dd>
<dt>prob</dt>
<dd>Probability mass for the interval (default 0.95).</dd>
<dt>nsim</dt>
<dd>Number of draws to simulate.</dd></dl>

Arguments

Highest Density Interval (HDI) — hdi

<dl>

<dt>object</dt>
<dd>A <code>qbrms_fit</code>.</dd>


<dt>parameters</dt>
<dd>Optional character vector; default uses all fixed effects.</dd>


<dt>prob</dt>
<dd>Probability mass for the interval (default 0.95).</dd>


<dt>nsim</dt>
<dd>Number of draws to simulate.</dd>

</dl>

hdi: Highest Density Interval (HDI)

Description

Usage

Value

Arguments