get_glm_mean

This function calculates the mean of the response variable for a generalized linear model (GLM)
based on the specified family. The calculation depends on whether the family is binomial or gaussian.

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_glm_mean function

<dl><dt>family_string</dt>
<dd>Character. The GLM family to use. Options are <code>"binomial"</code> or <code>"gaussian"</code>.</dd>
<dt>X</dt>
<dd>Matrix. The design matrix (predictors) for the GLM.</dd>
<dt>coefs</dt>
<dd>Numeric vector. The coefficients for the GLM.</dd></dl>

Arguments

Compute Mean Based on GLM Family — get_glm_mean

<dl>

<dt>family_string</dt>
<dd>Character. The GLM family to use. Options are <code>"binomial"</code> or <code>"gaussian"</code>.</dd>


<dt>X</dt>
<dd>Matrix. The design matrix (predictors) for the GLM.</dd>


<dt>coefs</dt>
<dd>Numeric vector. The coefficients for the GLM.</dd>

</dl>

get_glm_mean: Compute Mean Based on GLM Family

Description

Usage

Value

Arguments