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`tna`: An R package for Transition Network Analysis

tna is an R package for the analysis of relational dynamics through Transition Network Analysis (TNA). TNA provides tools for building TNA models, plotting transition networks, calculating centrality measures, and identifying dominant events and patterns. TNA statistical techniques (e.g., bootstrapping and permutation tests) ensure the reliability of observed insights and confirm that identified dynamics are meaningful. See (Saqr et al., 2025) for more details on TNA.

Resources

Check out our tutorials:

You can also try our Shiny app.

Installation

You can install the most recent stable version of tna from CRAN or the development version from GitHub by running one of the following:

install.packages("tna")

# install.packages("devtools")
# devtools::install_github("sonsoleslp/tna")

Example

Load the package

library("tna")

Example data

data("group_regulation", package = "tna")

Build a Markov model

tna_model <- tna(group_regulation)

summary(tna_model)

Plot the transition network

# Default plot
plot(tna_model)

# Optimized plot
plot(
  tna_model, cut = 0.2, minimum = 0.05, 
  edge.label.position = 0.8, edge.label.cex = 0.7
)

cent <- centralities(tna_model)

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Version

Install

install.packages('tna')

Monthly Downloads

404

Version

1.0.0

License

MIT + file LICENSE

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/sonsoleslp/tna/

Homepage

http://sonsoles.me/tna/

Maintainer

Sonsoles López-Pernas

Last Published

July 15th, 2025

Functions in tna (1.0.0)

Example Mixed Markov Model Fitted to the engagement Data

Build a Grouped Transition Network Analysis Model

Estimate Centrality Stability

plot.group_tna_communities

Plot Detected Communities

plot.group_tna_permutation

Plot Permutation Test Results

permutation_test

Compare Two Networks from Sequence Data using a Permutation Test

plot.tna_bootstrap

Plot a Bootstrapped Transition Network Analysis Model

plot.group_tna_bootstrap

Plot a Bootstrapped Grouped Transition Network Analysis Model

Plot a Grouped Transition Network Analysis Model

Import Wide Format Sequence Data as Long Format Sequence Data

plot.tna_centralities

Plot Centrality Measures

plot.tna_communities

Plot Communities

plot.tna_cliques

Plot Cliques of a TNA Network

Retrieve Statistics from a Mixture Markov Model (MMM)

plot.group_tna_cliques

Plot Found Cliques

plot_compare.group_tna

Plot the Difference Network Between Two Groups

plot.tna_comparison

Plot the Comparison of Two TNA Models or Matrices

plot.tna_stability

Plot Centrality Stability Results

Plot the Difference Network Between Two Models

Restore a Pruned Transition Network Analysis Model

compare.group_tna

Compare TNA Clusters with Comprehensive Metrics

plot.tna_permutation

Plot the Significant Differences from a Permutation Test

group_regulation_long

Example Long Data on Group Regulation

Compute User Sessions from Event Data

print.group_tna

Print a group_tna Object

plot.group_tna_centralities

Plot Centrality Measures

permutation_test.group_tna

Compare Networks using a Permutation Test

print.group_tna_permutation

Print Permutation Test Results

Create a Mosaic Plot of Transitions or Events

plot.group_tna_stability

Plot Centrality Stability Results

Plot a Transition Network Analysis Model

plot_frequencies.group_tna

Plot the Frequency Distribution of States

plot_frequencies

Plot the Frequency Distribution of States

print.group_tna_bootstrap

Print group_tna Bootstrap Results

Plot a Transition Network Model from a Matrix of Edge Weights

plot_mosaic.tna_data

Plot State Frequencies as a Mosaic Between Two Groups

print.summary.tna

Print a TNA Summary

Rename Clusters

print.summary.tna_bootstrap

Print a Bootstrap Summary

print.group_tna_cliques

Print Found Cliques

Create a Sequence Index Plot or a Distribution Plot

print.tna_cliques

Print Found Cliques of a TNA Network

print.tna_centralities

Print Centrality Measures

Calculate Summary of Network Metrics for a Transition Network

print.group_tna_communities

Print Detected Communities

print.tna_communities

Print Detected Communities

print.group_tna_stability

Print Centrality Stability Results

Simulate Data from a Transition Network Analysis Model

Prune a Transition Network based on Transition Probabilities

print.tna_stability

Print Centrality Stability Results

summary.group_tna_bootstrap

Summarize Bootstrap Results for a Grouped Transition Network

summary.group_tna

Calculate Summary of Network Metrics for a grouped Transition Network

print.tna_comparison

Print Comparison Results

print.summary.group_tna_bootstrap

Print a Bootstrap Summary for a Grouped Transition Network Model

Print a tna Object

print.tna_bootstrap

Print Bootstrap Results

plot_mosaic.group_tna

Plot State Frequencies as a Mosaic Between Two Groups

print.summary.group_tna

Print a Summary of a Grouped Transition Network Analysis Model

Print a TNA Data Object

print.group_tna_centralities

Print Centrality Measures

Restore Previous Pruning of a Transition Network Analysis Model

summary.tna_bootstrap

Summarize Bootstrap Results

The tna Package.

pruning_details

Print Detailed Information on the Pruning Results

Objects exported from other packages

print.tna_permutation

Print Permutation Test Results

Compare Two Matrices or TNA Models with Comprehensive Metrics

as.igraph.group_tna

Coerce a Specific Group from a group_tna Object into an igraph Object.

betweenness_network

Build and Visualize a Network with Edge Betweenness

Bootstrap Transition Networks from Sequence Data

Coerce a tna Object into an igraph Object.

Identify Cliques in a Transition Network

Community Detection for Transition Networks

Build a Transition Network Analysis Model

as.igraph.matrix

Coerce a Weight Matrix into an igraph Object.

Calculate Centrality Measures for a Transition Matrix

Plot a Histogram of Edge Weights for a group_tna Object.

group_regulation

Example Wide Data on Group Regulation

Example Data on Student Engagement

Plot a Histogram of Edge Weights in the Network