1. What is Spherical Data? | 2. Coordinate Convention | 3. Generating Synthetic Spherical Data | 4. Fitting the Spherical Model | 5. Out-of-Sample Evaluation | 6. Visualising Predictions | 7. Multiple Spherical Covariates | 8. Summary of Key Points

1. Loading the Package and Data | 2. Preparing the Data | 3. Training the Model | 4. Making Predictions and Evaluating Performance | 5. Visualising the Results

1. Generating a synthetic dataset | 2. Fitting the AddiVortes Model | 3. Out-of-Sample Prediction | 4. Visualising Prediction Performance | 5. Credible Intervals vs. Prediction Intervals

1. What is One-Hot Encoding? | 2. The catScaling Parameter | 3. A Synthetic Example | 4. Inspecting the Encoding | 5. Fitting the Model | 6. Making Predictions | 7. Handling Unseen Category Levels | 8. Effect of catScaling | 9. Summary of Key Points