prior_code

Format priors as qbrms prior() 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

prior_code function

<dl><dt>build</dt>
<dd>A 'qbrms_prior_build' returned by prior_build_from_beliefs()</dd>
<dt>object_name</dt>
<dd>Name of the object on the left-hand side (default "priors")</dd>
<dt>digits</dt>
<dd>Number of decimal places to print</dd>
<dt>include_comments</dt>
<dd>Logical; if TRUE, prepend a short comment header</dd></dl>

Arguments

Format priors as qbrms prior() code — prior_code

<dl>

<dt>build</dt>
<dd>A 'qbrms_prior_build' returned by prior_build_from_beliefs()</dd>


<dt>object_name</dt>
<dd>Name of the object on the left-hand side (default "priors")</dd>


<dt>digits</dt>
<dd>Number of decimal places to print</dd>


<dt>include_comments</dt>
<dd>Logical; if TRUE, prepend a short comment header</dd>

</dl>

prior_code: Format priors as qbrms prior() code

Description

Usage

Value

Arguments