fit_fallback_model

Very simple fitting strategies used as a last resort when primary fitting
fails. These provide coefficient means and approximate standard deviations
sufficient for downstream summaries and plotting.

internal

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

fit_fallback_model function

<dl><dt>formula</dt>
<dd>A model formula.</dd>
<dt>data</dt>
<dd>A <code>data.frame</code>.</dd>
<dt>family</dt>
<dd>A family object.</dd>
<dt>verbose</dt>
<dd>Logical; print progress information.</dd></dl>

Arguments

Fallback model fitting for edge cases — fit_fallback_model

<dl>

<dt>formula</dt>
<dd>A model formula.</dd>


<dt>data</dt>
<dd>A <code>data.frame</code>.</dd>


<dt>family</dt>
<dd>A family object.</dd>


<dt>verbose</dt>
<dd>Logical; print progress information.</dd>

</dl>

fit_fallback_model: Fallback model fitting for edge cases

Description

Usage

Value

Arguments