Conceptual Guides

Conceptual guides explain method choices. Function pages document exact calls and parameters. Use this page to start from your research goal, then move to the pages you need.

Learn in Order

If you are new to sequence analysis, read these pages first:

• Basic Concepts
• Timing, Duration, and Order
• Sequence Summary Statistics vs Sequence Characteristics Indicators
• Statistics Is More Than Models
• Sequence Analysis vs. Regression

Then move into sequence comparison and clustering:

• Dissimilarity Measures
• Distance Matrices
• Normalizing Sequences
• Computational Complexity of Dissimilarity Measures if you are working with large samples
• Cluster Analysis Methods
• Cluster Quality Indicators
• Understanding CLARA
• Reporting Results of the Typical Workflow when you write up the results

For model-based sequence analysis, start here:

• Latent Class Analysis
• Markov Chains
• Hidden Markov Models
• Sequence Analysis vs. LCA vs. HMM

For event-history style extensions, see:

• Sequence History Analysis
• Sequence Analysis Multi-state Model

Start by Goal

Goal	Start with	Then use
Describe and visualize trajectories	Basic Concepts, Timing, Duration, and Order, Sequence Summary Statistics vs Sequence Characteristics Indicators	How to Read Sequence Plots, Visualization Gallery, Sequence Summary Statistics, Sequence Characteristics Indicators
Compare and cluster whole sequences	Dissimilarity Measures, Distance Matrices	get_distance_matrix(), Cluster Analysis Methods, Cluster Quality Indicators
Scale clustering to large datasets	Big Data Tools, Check Uniqueness Rate	Understanding CLARA, CLARA, Scaling Multidomain Workflows
Compare predefined groups	Group Comparison, Discrepancy Analysis	Sequence Analysis vs. Regression, Decomposition
Model latent dynamics	Markov Chains, Hidden Markov Models	Markov Chain Models
Work with multidomain or relational trajectories	Basic Concepts	Multidomain or Polyadic Sequence Analysis, Hierarchical and Relational Sequence Analysis
Turn sequences into regression-ready variables	Sequence Analysis vs. Regression	From Sequences to Variables, Feature Extraction and Selection
Mine frequent event patterns	Basic Concepts	Event Sequences
Model transition histories or spell survival	Sequence History Analysis, Sequence Analysis Multi-state Model	Event History Analysis
Report robustness to timing error	Dissimilarity Measures	Timing Uncertainty
Write up methods for a paper	Reporting Results of the Typical Workflow	Cluster Quality Indicators, How to Cite

Run Code

Use View Our Tutorials Online for full Colab and GitHub examples. For a compact in-doc example, start with the Quickstart.