get_glm_sample_data

This function generates sample data for a specified GLM family. It can generate
binomial or Gaussian distributed data based on the provided parameters.

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_sample_data function

<dl><dt>family_string</dt>
<dd>Character. The family of the GLM. Options are <code>"binomial"</code> or <code>"gaussian"</code>.</dd>
<dt>n</dt>
<dd>Integer. The number of samples to generate.</dd>
<dt>mean</dt>
<dd>Numeric. The mean of the distribution (used for both binomial and Gaussian).</dd>
<dt>sd</dt>
<dd>Numeric. The standard deviation of the distribution (used only for Gaussian).</dd></dl>

Arguments

Generate Sample Data for GLM — get_glm_sample_data

<dl>

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


<dt>n</dt>
<dd>Integer. The number of samples to generate.</dd>


<dt>mean</dt>
<dd>Numeric. The mean of the distribution (used for both binomial and Gaussian).</dd>


<dt>sd</dt>
<dd>Numeric. The standard deviation of the distribution (used only for Gaussian).</dd>

</dl>

get_glm_sample_data: Generate Sample Data for GLM

Description

Usage

Value

Arguments