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.

Bayesian Package for Network Changepoint Analysis

package-ubuntu-20.04-r-4.0.5#cran#NetworkChange-0.7

Update time-constant regression parameters

<table summary="R argblock">
<tr valign="top">
<td><code>Z</code></td>
<td>
Degree corrected response tensor
</td>
</tr>
<tr valign="top">
<td><code>MU</code></td>
<td>
Mean array
</td>
</tr>
<tr valign="top">
<td><code>s2</code></td>
<td>
Error variance
</td>
</tr>
<tr valign="top">
<td><code>XtX</code></td>
<td>
X'X
</td>
</tr>
<tr valign="top">
<td><code>b0</code></td>
<td>
Prior mean of beta
</td>
</tr>
<tr valign="top">
<td><code>B0</code></td>
<td>
Prior variance of beta
</td>
</tr>
</table>

A vector of regression parameters

package-ubuntu-20.04-r-4.0.5#cran#NetworkChange-0.7#docs#updateb

updateb

Description

Usage

Arguments

Value

NetworkChange

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`Z`	Degree corrected response tensor
`MU`	Mean array
`s2`	Error variance
`XtX`	X'X
`b0`	Prior mean of beta
`B0`	Prior variance of beta