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NetworkChange (version 1.0.0)

Bayesian Package for Network Changepoint Analysis

Description

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.

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Version

Install

install.packages('NetworkChange')

Monthly Downloads

391

Version

1.0.0

License

GPL-3

Maintainer

Jong Hee Park

Last Published

January 21st, 2026

Functions in NetworkChange (1.0.0)

plotU

Plot of latent node positions
scale_color_networkchange

NetworkChange Discrete Color Scale
startS

Sample a starting value of hidden states
updateVm

Update V from a change-point network process
startUV

Starting values of U and V
updateb

Update time-constant regression parameters
updateUm

Regime-specific latent node positions
updateV

Update layer specific network generation rules
kmeansU

K-mean clustering of latent node positions
updates2m

Update regime-specific variance
drawRegimeRaw

Plot of network by hidden regime
updatebm

Update regime-changing regression parameters
scale_color_networkchange_c

NetworkChange Continuous Color Scale
drawPostAnalysis

Plot of latent node cluster
scale_fill_networkchange

NetworkChange Discrete Fill Scale
updateP

Update transition matrix
theme_networkchange

NetworkChange ggplot2 Theme
updateU

Update time-constant latent node positions
BreakPointLoss

Compute the Average Loss of Hidden State Changes from Expected Break Points
BreakDiagnostic

Detect a break number using different metrics
ULUstateSample.mpfr

Hidden State Sampler with precision
combineVm

Combine regime-specific V matrices efficiently
ULUstateSample

Hidden State Sampler
plotV

Plot of layer-specific network generation rules.
NetworkStatic

Degree-corrected multilinear tensor model
NetworkChangeRobust

Changepoint analysis of a degree-corrected multilinear tensor model with t-distributed error
MarginalCompare

Compare Log Marginal Likelihood
NetworkChange

Changepoint analysis of a degree-corrected multilinear tensor model
WaicCompare

Compare WAIC
PostwarAlly

Postwar Alliance Network (1846 - 2012)
plotnetarray

Plot of network array data
updateS

Update latent states
MakeBlockNetworkChange

Build a synthetic block-structured temporal data with breaks
multiplot

Printing multiple ggplots in one file (DEPRECATED)
MajorAlly

Major Power Alliance Network (1816 - 2012)
plotContour

Contour plot of latent node positions