Tutorial Series

This five-part tutorial series walks you through the full lrdbenchmark workflow—from generating synthetic and realistic long-range dependent data to evaluating estimators with statistical diagnostics and publishing leaderboard-quality reports. Follow the modules in order for a guided learning path, or jump to the topic most relevant to your needs.

Multi-Part Tutorials

• Data Generation and Visualisation
  • Overview
  • Table of Contents
  • 1. Setup and Imports
  • 2. Theoretical Background
  • 3. Fractional Brownian Motion (FBM)
  • 4. Comparative Analysis
  • 5. Summary and Next Steps
• Estimation and Statistical Validation
  • Overview
  • Table of Contents
  • 1. Setup and Imports
  • 2. Estimator Categories Overview
  • 3. Classical Estimators
  • 4. Machine Learning Estimators
  • 5. Neural Network Estimators
  • 6. Performance Comparison
  • 7. Decision Guidelines
  • 8. Summary and Next Steps
• Custom Models and Estimators
  • Overview
  • Table of Contents
  • 1. Setup and Imports
  • 2. Understanding Base Classes
  • 3. Custom Data Model Example
  • 4. Custom Classical Estimator
  • 5. Summary and Next Steps
• Comprehensive Estimator Benchmarking
  • Overview
  • Table of Contents
  • 1. Setup and Imports
  • 2. Benchmark System Overview
  • 3. Contamination Robustness Testing
  • 4. Summary and Next Steps
  • Stratified and Robustness Diagnostics
• Leaderboard Generation
  • Overview
  • Table of Contents
  • 1. Setup and Imports
  • 2. Loading Benchmark Results
  • 3. Creating Performance Rankings
  • 4. Visualization and Export
  • 5. Summary and Next Steps
  • Additional Analyses
• Biomedical Preprocessing Tutorial
  • Loading the Surrogate Datasets
  • Preparing the Signals
  • Benchmarking the Cleaned Series