sample_c_two

Sample divergence function parameter c for a(t) = c / (1-t)^2 through Gibbs sampler

Implements a Bayesian algorithm for overcoming weak separation in Bayesian latent class analysis.
Reference: Li et al. (2023) <arXiv:2306.04700>.

Mengbing Li

ddtlcm

Latent Class Analysis with Dirichlet Diffusion Tree Process
Prior

Briana Stephenson

Zhenke Wu

sample_c_two function

<dl><dt>shape0</dt>
<dd>shape of the Inverse-Gamma prior</dd>
<dt>rate0</dt>
<dd>rate of the Inverse-Gamma prior</dd>
<dt>tree_structure</dt>
<dd>a data.frame containing the divergence times and number of
data points to the left and right branches of internal nodes on the tree</dd></dl>

Arguments

Sample divergence function parameter c for a(t) = c / (1-t)^2 through Gibbs sampler — sample_c_two

<dl>

<dt>shape0</dt>
<dd>shape of the Inverse-Gamma prior</dd>


<dt>rate0</dt>
<dd>rate of the Inverse-Gamma prior</dd>


<dt>tree_structure</dt>
<dd>a data.frame containing the divergence times and number of
data points to the left and right branches of internal nodes on the tree</dd>

</dl>

sample_c_two: Sample divergence function parameter c for a(t) = c / (1-t)^2 through Gibbs sampler

Description

Usage

Value

Arguments