qbrmb_regularised

Convenience wrapper around <code>qbrmb</code> using the "enhanced"
regularisation strategy and a stronger default regularisation strength.

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

qbrmb_regularised function

<dl><dt>formula</dt>
<dd>Model formula with random effects (lme4-style).</dd>
<dt>data</dt>
<dd>Data frame containing the variables in the model.</dd>
<dt>verbose</dt>
<dd>Logical; if <code>TRUE</code>, show detailed diagnostics.</dd>
<dt>...</dt>
<dd>Additional arguments passed to <code>qbrmb</code>.</dd></dl>

Arguments

Regularised binomial mixed-effects (enhanced strategy) — qbrmb_regularised

<dl>

<dt>formula</dt>
<dd>Model formula with random effects (lme4-style).</dd>


<dt>data</dt>
<dd>Data frame containing the variables in the model.</dd>


<dt>verbose</dt>
<dd>Logical; if <code>TRUE</code>, show detailed diagnostics.</dd>


<dt>...</dt>
<dd>Additional arguments passed to <code>qbrmb</code>.</dd>

</dl>

qbrmb_regularised: Regularised binomial mixed-effects (enhanced strategy)

Description

Usage

Value

Arguments