Package: spatialcvR 0.1.0

Overview | Model Evaluation Metrics | Available Metrics | Calculating Metrics | Understanding the Metrics | Spatial Cross-Validation Workflow | Step 1: Create Folds | Step 2: Train and Evaluate Models | Step 3: Aggregate Results | Comparing CV Methods | Using compare_cv | Interpreting the Comparison | Spatial Residual Diagnostics | Calculating Spatial Residuals | Visualizing Residuals | Interpreting Residual Patterns | Practical Example: Complete Workflow | Scenario: Predicting Crop Yield | Advanced Topics | Cross-Method Comparison | Performance vs. Spatial Separation Trade-off | Best Practices | 1. Always Compare with Random CV | 2. Check for Spatial Leakage | 3. Analyze Residuals Spatially | 4. Consider the Prediction Context | 5. Document Your Approach | Common Pitfalls | Pitfall 1: Ignoring Spatial Dependence | Pitfall 2: Overfitting to Spatial Structure | Pitfall 3: Inappropriate CRS | Pitfall 4: Small Sample Sizes | Next Steps | Key Takeaways

Introduction | The Spatial Dependence Problem | Tobler's First Law of Geography | Why Traditional Cross-Validation Fails | Consequences of Spatial Leakage | The Solution: Spatial Cross-Validation | When to Use Spatial Cross-Validation | Common Applications | What spatialcvR Provides | Quick Example | Next Steps | References | Key Takeaways

Overview | Available Methods | Setup | Spatial Block Cross-Validation | Concept | When to Use | Basic Usage | Controlling Block Size | Assignment Strategies | Buffered Cross-Validation | Important Notes | Spatial Clustering Cross-Validation | Understanding Cluster Assignment | Random Spatial Split (Baseline) | Choosing the Right Method | Decision Flowchart | Method Comparison | Visualizing Folds | Practical Tips | Start Simple | Adjust Based on Data Characteristics | Always Compare with Random CV | Common Issues and Solutions | Issue: Too few observations per fold | Issue: Uneven fold sizes | Issue: Geographic gaps in training data | Next Steps | Key Takeaways

Understanding Spatial Leakage | What is Spatial Leakage? | Definition | Consequences | Detecting Spatial Leakage | Basic Usage | Understanding the Output | Analyzing Spatial Distances | Calculating Distances | Distance Statistics Explained | Interpreting Distance Values | Customizing Leakage Detection | Setting Custom Thresholds | Custom Risk Levels | Comparing Different CV Methods | Spatial vs Random CV | Expected Differences | Case Studies | Case 1: High Spatial Leakage | Case 2: Low Spatial Leakage | Addressing Spatial Leakage | Recommendations by Risk Level | Low Risk | Moderate Risk | High Risk | Practical Solutions | Integration with Model Evaluation | Full Workflow Example | Important Considerations | Coordinate Reference Systems | Threshold Selection | Multiple Metrics | Next Steps | Key Takeaways