create_dummy_data_for_priors

Internal function to create dummy data that preserves structure.

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

create_dummy_data_for_priors function

<dl><dt>formula</dt>
<dd>Model formula.</dd>
<dt>data</dt>
<dd>Original data.</dd>
<dt>n_dummy</dt>
<dd>Number of dummy observations.</dd>
<dt>family_name</dt>
<dd>The name of the model family (e.g., "poisson").</dd>
<dt>verbose</dt>
<dd>Logical, whether to print messages.</dd></dl>

Arguments

Create Dummy Data for Prior Predictive Checks — create_dummy_data_for_priors

<dl>

<dt>formula</dt>
<dd>Model formula.</dd>


<dt>data</dt>
<dd>Original data.</dd>


<dt>n_dummy</dt>
<dd>Number of dummy observations.</dd>


<dt>family_name</dt>
<dd>The name of the model family (e.g., "poisson").</dd>


<dt>verbose</dt>
<dd>Logical, whether to print messages.</dd>

</dl>

create_dummy_data_for_priors: Create Dummy Data for Prior Predictive Checks

Description

Usage

Value

Arguments