updatebm

Network changepoint analysis for undirected network data. The package implements a hidden Markov network change point model (Park and Sohn (2020)). Functions for break number detection using the approximate marginal likelihood and WAIC are also provided. This version includes performance optimizations with vectorized MCMC operations and modern ggplot2-based visualizations with colorblind-friendly palettes.

Jong Hee Park

NetworkChange

Bayesian Package for Network Changepoint Analysis

Yunkyu Sohn

updatebm function

<dl><dt>ns</dt>
<dd>The number of hidden states</dd>
<dt>K</dt>
<dd>The dimensionality of Z</dd>
<dt>s</dt>
<dd>Latent state vector</dd>
<dt>s2</dt>
<dd>The variance of error</dd>
<dt>B0</dt>
<dd>The prior variance of beta</dd>
<dt>p</dt>
<dd>The rank of X</dd>
<dt>ZU</dt>
<dd>Z - ULU</dd></dl>

Arguments

Update regime-changing regression parameters — updatebm

<dl>

<dt>ns</dt>
<dd>The number of hidden states</dd>


<dt>K</dt>
<dd>The dimensionality of Z</dd>


<dt>s</dt>
<dd>Latent state vector</dd>


<dt>s2</dt>
<dd>The variance of error</dd>


<dt>B0</dt>
<dd>The prior variance of beta</dd>


<dt>p</dt>
<dd>The rank of X</dd>


<dt>ZU</dt>
<dd>Z - ULU</dd>

</dl>

updatebm: Update regime-changing regression parameters

Description

Usage

Value

Arguments