get_adjusted_cat_init

This function adjusts the categorical initialization by creating a model frame
for the predictors specified in the right-hand side of the formula and splits
the adjusted data into observed and synthetic parts.

To improve estimation accuracy and stability in statistical modeling, catalytic prior distributions are employed, integrating observed data with synthetic data generated from a simpler model's predictive distribution. This approach enhances model robustness, stability, and flexibility in complex data scenarios. The catalytic prior distributions are introduced by 'Huang et al.' (2020, <doi:10.1073/pnas.1920913117>), Li and Huang (2023, <doi:10.48550/arXiv.2312.01411>).

Dongming Huang

catalytic

Tools for Applying Catalytic Priors in Statistical Modeling

Yitong Wu

Weihao Li

Ministry of Education, Singapore 

get_adjusted_cat_init function

<dl><dt>cat_init</dt>
<dd>The object generated from <code>cat_glm_initialization</code>, <code>cat_cox_initialization</code> or <code>cat_lmm_initialization</code></dd>
<dt>formula_rhs</dt>
<dd>A formula specifying the right-hand side of the model for predictors.</dd></dl>

Arguments

Adjusted Cat Initialization — get_adjusted_cat_init

<dl>

<dt>cat_init</dt>
<dd>The object generated from <code>cat_glm_initialization</code>, <code>cat_cox_initialization</code> or <code>cat_lmm_initialization</code></dd>


<dt>formula_rhs</dt>
<dd>A formula specifying the right-hand side of the model for predictors.</dd>

</dl>

get_adjusted_cat_init: Adjusted Cat Initialization

Description

Usage

Value

Arguments