process_ordinal_priors_adaptive

Enhanced Prior Processing with Adaptive Centering - CORRECTED VERSION

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

process_ordinal_priors_adaptive function

<dl><dt>prior</dt>
<dd>Prior specifications using qbrms prior syntax</dd>
<dt>tmb_data</dt>
<dd>Prepared TMB data structure</dd>
<dt>data</dt>
<dd>Original data frame</dd>
<dt>formula_parts</dt>
<dd>Parsed formula components</dd>
<dt>verbose</dt>
<dd>Logical; print progress messages</dd></dl>

Arguments

Enhanced Prior Processing with Adaptive Centering - CORRECTED VERSION — process_ordinal_priors_adaptive

<dl>

<dt>prior</dt>
<dd>Prior specifications using qbrms prior syntax</dd>


<dt>tmb_data</dt>
<dd>Prepared TMB data structure</dd>


<dt>data</dt>
<dd>Original data frame</dd>


<dt>formula_parts</dt>
<dd>Parsed formula components</dd>


<dt>verbose</dt>
<dd>Logical; print progress messages</dd>

</dl>

process_ordinal_priors_adaptive: Enhanced Prior Processing with Adaptive Centering - CORRECTED VERSION

Description

Usage

Value

Arguments