Transition Network Analysis (TNA)
Coerce a Specific Group from a group_tna Object into an igraph Obj...
Coerce a Weight Matrix into an igraph Object.
Coerce a tna Object into an igraph Object.
Build and Visualize a Network with Edge Betweenness
Bootstrap Cliques of Transition Networks from Sequence Data
Bootstrap Transition Networks from Sequence Data
Build a Transition Network Analysis Model
Calculate Centrality Measures for a Transition Matrix
Identify Cliques in a Transition Network
Cluster Sequences via Dissimilarity Matrix based on String Distances
Community Detection for Transition Networks
Compare Sequences Between Groups
Compare Grouped TNA Models with Comprehensive Metrics
Compare Two Matrices or TNA Models with Comprehensive Metrics
Restore a Pruned Transition Network Analysis Model
Estimate Centrality Stability
Build a Grouped Transition Network Analysis Model
Plot a Histogram of Edge Weights for a group_tna Object.
Plot a Histogram of Edge Weights in the Network
Import Wide Format Sequence Data as Long Format Sequence Data
Import One-Hot Data and Create a Co-Occurrence Network Model
Retrieve Statistics from a Mixture Markov Model (MMM)
Compare Networks using a Permutation Test
Compare Two Networks from Sequence Data using a Permutation Test
Plot an Association Network
Plot the Difference Network Between Two Groups
Plot the Difference Network Between Two Models
Plot the Frequency Distribution of States
Plot the Frequency Distribution of States
Plot a Transition Network Model from a Matrix of Edge Weights
Plot State Frequencies as a Mosaic Between Two Groups
Create a Mosaic Plot of Transitions or Events
Plot State Frequencies as a Mosaic Between Two Groups
Create a Sequence Index Plot or a Distribution Plot
Plot a Bootstrapped Grouped Transition Network Analysis Model
Plot Centrality Measures
Plot Found Cliques
Plot Detected Communities
Plot Permutation Test Results
Plot Centrality Stability Results
Plot a Grouped Transition Network Analysis Model
Plot a Bootstrapped Transition Network Analysis Model
Plot Centrality Measures
Plot Cliques of a TNA Network
Plot Communities
Plot the Comparison of Two TNA Models or Matrices
Plot the Significant Differences from a Permutation Test
Plot a Sequence Comparison
Plot Centrality Stability Results
Plot a Transition Network Analysis Model
Compute User Sessions from Event Data
Print group_tna Bootstrap Results
Print Centrality Measures
Print Found Cliques
Print Detected Communities
Print Permutation Test Results
Print Centrality Stability Results
Print a group_tna Object
Print a Bootstrap Summary for a Grouped Transition Network Model
Print a Summary of a Grouped Transition Network Analysis Model
Print a Bootstrap Summary
Print a TNA Summary
Print Bootstrap Results
Print Centrality Measures
Print Found Cliques of a TNA Network
Print Detected Communities
Print Comparison Results
Print a TNA Data Object
Print Permutation Test Results
Print a Comparison of Sequences
Print Centrality Stability Results
Print a tna Object
Prune a Transition Network based on Transition Probabilities
Print Detailed Information on the Pruning Results
Objects exported from other packages
Rename Groups
Restore Previous Pruning of a Transition Network Analysis Model
Simulate Data from a Transition Network Analysis Model
Build a Social Network Analysis Model
Summarize Bootstrap Results for a Grouped Transition Network
Calculate Summary of Network Metrics for a grouped Transition Network
Summarize Bootstrap Results
Calculate Summary of Network Metrics for a Transition Network
The tna Package.
Provides tools for performing Transition Network Analysis (TNA) to study relational dynamics, including functions for building and plotting TNA models, 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) <doi:10.1145/3706468.3706513> for more details on TNA.
Useful links