Garmin Analysis Documentation

Bayesian analysis of health and fitness data from Garmin devices
🎯 Enhanced Sensitivity Model Now Primary: All documentation has been updated to feature the enhanced sensitivity model with conservative sampling (adapt_delta=0.99, max_treedepth=12). This model provides reliable inference with proper uncertainty quantification and smooth continuous predictions.
🚧 Playground Work-in-Progress Notice: This documentation and associated models represent an experimental playground for Bayesian analysis of personal health data. Models, visualizations, and conclusions are actively evolving and should be considered exploratory research rather than production-ready analysis.

🌟 Enhanced Sensitivity Model (Primary)

Featured Model: Comprehensive analysis of enhanced sensitivity model with conservative sampling (adapt_delta=0.99) and smooth continuous predictions. This is now the primary model for all analysis.

View Primary Model Overview →

📊 Enhanced Model Comprehensive Report

Detailed analysis of enhanced sensitivity model with parameter estimates, variance decomposition, convergence diagnostics, and model recommendations.

View Comprehensive Report →

📈 Enhanced Fitness Time Series

Enhanced sensitivity model fitness time series with conservative sampling. Shows smooth predictions, component breakdown, and reliable uncertainty quantification from adapt_delta=0.99 sampling.

View Enhanced Visualizations →

Technical Model Documentation

Complete mathematical and computational documentation of the four-fitness state-space model. Includes equations, Stan implementation, Python pipeline, and parameter sensitivity analysis.

View Technical Documentation →

Project Guidelines (CLAUDE.md)

Project-specific instructions for AI assistants, including tooling requirements, project structure, and development methodologies.

View HTML

Workout Data Report

Analysis of Garmin workout data quality, aggregation methods, and recommendations for modeling. Focuses on strength training data for cross-lagged time-series analysis.

View HTML

Enhanced Sensitivity Analysis

Comprehensive analysis of enhanced sensitivity model with conservative sampling (adapt_delta=0.99) and smooth continuous predictions. Includes detailed parameter estimates, variance decomposition, and model recommendations.

View Enhanced Analysis →

Consolidation Summary

Summary of model and report consolidation focusing on the four-fitness state-space model with baseline fitness equilibrium at 0. Documents the cleanup process and new structure.

View Summary