Function Reference

Use this page to find the Sequenzo function, class, or workflow page for a task.

New to Sequenzo? Start with the Quickstart or Typical Workflow. Use this page when you already know the task and need the right function family.

Data Preparation

Task	Main pages
Convert between wide and long formats	wide_to_long_format_data() and long_to_wide_format_data()
Check missing values	summarize_missing_values()
Assign stable IDs	assign_unique_ids()
Clean time-column names	clean_time_columns_auto()
Replace numeric cluster IDs with labels	replace_cluster_id_by_labels()
Work with weights	Working with Weighted Data

Typical Workflow

Task	Main entry points
Define categorical sequence data	SequenceData
Compute pairwise sequence dissimilarities	get_distance_matrix()
Cluster sequences hierarchically	Cluster
Cluster with k-medoids	KMedoids
Evaluate cluster quality	ClusterQuality
Inspect and summarize cluster results	ClusterResults

Sequence Operations and Distances

Task	Main pages
Concatenate, decompose, recode, shift, and align sequences	Sequence Operations
Build substitution-cost matrices or inspect distance helpers	Dissimilarity Helper Functions
Analyze forward divergence and backward convergence	Prefix and Suffix Trees
Choose and normalize sequence dissimilarities	get_distance_matrix()

Descriptive Statistics and Indicators

Task	Main pages
Compute sequence characteristics indicators	Sequence Characteristics Indicators
Compute weighted descriptive statistics	Sequence Summary Statistics
Compare Sequenzo and TraMineR naming	Functions Comparison

Visualization

Task	Main pages
Browse available plot types	Visualization Gallery
Customize palettes and plot options	Visualization Tools
Plot individual sequences, state distributions, modal states, medoids, and transitions	Visualization Tools

Clustering and Typologies

Task	Main pages
Fit one hierarchical or k-medoids solution	Cluster, KMedoids
Compare cluster counts and clustering methods	Clustering Extensions
Work with fuzzy memberships or property-based typologies	Clustering Extensions
Convert sequence typologies into regression variables	From Sequences to Variables
Select representative observed sequences	Representative Sequences

Inference, Group Comparison, and Decomposition

Task	Main pages
Run discrepancy analysis and permutation tests	Discrepancy Analysis
Compare sequence groups with likelihood-ratio or BIC tests	Group Comparison
Decompose group differences in sequence outcomes	Decomposition
Extract and select interpretable sequence features	Feature Extraction and Selection

Model-Based Sequence Analysis

Task	Main pages
Build and fit HMMs, MHMMs, NHMMs, or MNHMMs	Markov Chain Models
Map Sequenzo functions to R seqHMM	Sequenzo and seqHMM Mapping
Compare HMM-family models	Model Comparison
Bootstrap HMM-family models	Bootstrap Model

Event Sequences, Event History, and Survival

Task	Main pages
Mine event subsequences and event-pattern frequencies	Event Sequences
Convert between event sequences and TSE format	Event Sequence Helpers
Analyze sequence histories, SAMM windows, or spell survival	Sequence History, SAMM, and Spell Survival

Multidomain, Polyadic, and Relational Analysis

Task	Main pages
Compare domains or build multidomain distances	Multidomain or Polyadic Sequence Analysis
Build CAT, DAT, or IDCD distances	CAT, DAT, IDCD
Scale multidomain workflows	Scaling Multidomain Workflows
Analyze level-1 by level-2 relational trajectories	Hierarchical and Relational Sequence Analysis

Big Data Tools

Task	Main pages
Use CLARA for large single-domain sequence clustering	CLARA
Plan large multidomain sequence analysis	Scaling Multidomain Workflows
Choose scalable clustering tools	Big Data Tools

Uncertainty

Task	Main pages
Assess sensitivity to transition-timing error	Timing Uncertainty

Notes on Completeness

This reference prioritizes stable, user-facing functions and workflows. Low-level helpers are documented on module pages when they are not central enough for a separate page.

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