Package index • tna

Basic functions

tna-package: The tna Package.

build_model() tna() ftna() ctna() atna() tsn(): Build a Transition Network Analysis Model

print(<tna>): Print a tna Object

plot(<tna>): Plot a Transition Network Analysis Model

hist(<tna>): Plot a Histogram of Edge Weights in the Network

sna(): Build a Social Network Analysis Model

print(<summary.tna>): Print a TNA Summary

plot_frequencies(): Plot the Frequency Distribution of States

plot_frequencies(<group_tna>): Plot the Frequency Distribution of States

plot_mosaic(): Create a Mosaic Plot of Transitions or Events

plot_mosaic(<tna_data>): Plot State Frequencies as a Mosaic Between Two Groups

plot_associations(): Plot an Association Network

print(<group_tna>): Print a group_tna Object

plot(<group_tna>): Plot a Grouped Transition Network Analysis Model

summary(<group_tna>): Calculate Summary of Network Metrics for a grouped Transition Network

hist(<group_tna>): Plot a Histogram of Edge Weights for a group_tna Object.

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

plot_sequences(): Create a Sequence Index Plot or a Distribution Plot

Importing/generating data

import_data(): Import Wide Format Sequence Data as Long Format Sequence Data

import_onehot(): Import One-Hot Data and Create a Co-Occurrence Network Model

prepare_data(): Compute User Sessions from Event Data

print(<tna_data>): Print a TNA Data Object

simulate(<tna>): Simulate Data from a Transition Network Analysis Model

summary(<tna>): Calculate Summary of Network Metrics for a Transition Network

Centralities

centralities(): Calculate Centrality Measures for a Transition Matrix

betweenness_network(): Build and Visualize a Network with Edge Betweenness

print(<tna_centralities>): Print Centrality Measures

plot(<tna_centralities>): Plot Centrality Measures

print(<group_tna_centralities>): Print Centrality Measures

plot(<group_tna_centralities>): Plot Centrality Measures

Communities

communities(): Community Detection for Transition Networks

print(<tna_communities>): Print Detected Communities

plot(<tna_communities>): Plot Communities

print(<group_tna_communities>): Print Detected Communities

plot(<group_tna_communities>): Plot Detected Communities

Cliques

cliques(): Identify Cliques in a Transition Network

print(<tna_cliques>): Print Found Cliques of a TNA Network

plot(<tna_cliques>): Plot Cliques of a TNA Network

print(<group_tna_cliques>): Print Found Cliques

plot(<group_tna_cliques>): Plot Found Cliques

Clusters

cluster_sequences() print(<tna_clustering>): Cluster Sequences via Dissimilarity Matrix based on String Distances

mmm_stats(): Retrieve Statistics from a Mixture Markov Model (MMM)

Comparison

compare(): Compare Two Matrices or TNA Models with Comprehensive Metrics

compare(<group_tna>): Compare Grouped TNA Models with Comprehensive Metrics

compare_sequences(): Compare Sequences Between Groups

print(<tna_comparison>): Print Comparison Results

print(<tna_sequence_comparison>): Print a Comparison of Sequences

plot_compare(): Plot the Difference Network Between Two Models

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_sequence_comparison>): Plot a Sequence Comparison

Validation

permutation_test(): Compare Two Networks from Sequence Data using a Permutation Test

permutation_test(<group_tna>): Compare Networks using a Permutation Test

print(<tna_permutation>): Print Permutation Test Results

print(<group_tna_permutation>): Print Permutation Test Results

plot(<tna_permutation>): Plot the Significant Differences from a Permutation Test

plot(<group_tna_permutation>): Plot Permutation Test Results

print(<tna_bootstrap>): Print Bootstrap Results

print(<summary.tna_bootstrap>): Print a Bootstrap Summary

print(<summary.group_tna_bootstrap>): Print a Bootstrap Summary for a Grouped Transition Network Model

print(<tna_stability>): Print Centrality Stability Results

plot(<tna_stability>): Plot Centrality Stability Results

print(<group_tna_bootstrap>): Print group_tna Bootstrap Results

print(<group_tna_stability>): Print Centrality Stability Results

plot(<group_tna_stability>): Plot Centrality Stability Results

estimate_cs() estimate_centrality_stability(): Estimate Centrality Stability

prune(): Prune a Transition Network based on Transition Probabilities

deprune() reprune(<tna>): Restore a Pruned Transition Network Analysis Model

reprune(): Restore Previous Pruning of a Transition Network Analysis Model

pruning_details(): Print Detailed Information on the Pruning Results

bootstrap(): Bootstrap Transition Networks from Sequence Data

bootstrap_cliques(): Bootstrap Cliques of Transition Networks from Sequence Data

plot(<tna_bootstrap>): Plot a Bootstrapped Transition Network Analysis Model

plot(<group_tna_bootstrap>): Plot a Bootstrapped Grouped Transition Network Analysis Model

summary(<tna_bootstrap>): Summarize Bootstrap Results

summary(<group_tna_bootstrap>): Summarize Bootstrap Results for a Grouped Transition Network

Groups

group_model() group_tna() group_ftna() group_ctna() group_atna(): Build a Grouped Transition Network Analysis Model

rename_groups(): Rename Groups

Helpers

as.igraph(<group_tna>): Coerce a Specific Group from a group_tna Object into an igraph Object.

as.igraph(<matrix>): Coerce a Weight Matrix into an igraph Object.

as.igraph(<tna>): Coerce a tna Object into an igraph Object.

Datasets

engagement: Example Data on Student Engagement

engagement_mmm: Example Mixed Markov Model Fitted to the engagement Data

group_regulation: Example Wide Data on Group Regulation

group_regulation_long: Example Long Data on Group Regulation