Package: fmrilss 0.1.0

Why fmrilss? | Quick example | Create a rapid event design | Add baseline and nuisance regressors | Simulate data with known ground truth | Run LSS | LSS vs standard GLM | Prewhitening | Computational backends | OASIS: single-pass LSS with extras | Nuisance pre-projection | Next steps | References

Motivation | Prerequisites | Computational Intuition | Visual Comparison of Computational Scaling | Classical LSS Recap | Single-Basis OASIS Algebra | Fractional Ridge | Standard Errors | Multi-Basis Extension | [\begin | HRF-Aware Design Construction | AR(1) Whitening | Diagnostics Output | Algorithm Summary | Complexity and Memory | Next Steps | References

The Problem | Step 1: Build the Shared Basis | Visualizing the Basis | Choosing the Rank | Library Coverage | Step 2: Generate Synthetic Data | Step 3: Run the SBHM Pipeline | Step 4: Evaluate Recovery | Matching Accuracy | Matching Confidence | Amplitude Recovery | Recovered HRF Shapes | Library Manifold | Soft Assignment for Ambiguous Voxels | Shape Estimation Strategies | Low-Confidence Gating | Amplitude Policy | Returning Coefficients for Custom Analysis | Parameter Quick Reference | Performance Considerations | Prewhitening | References | Summary

What OASIS Adds Over Plain LSS | Synthetic Data | Basic OASIS Call | Equivalence to LSS | Ridge Regularization | Absolute Ridge | Fractional Ridge | Multi-Basis HRFs | FIR Basis | HRF Grid Search | Multiple Conditions | Standard Errors | Prewhitening | When to Use OASIS | Next Steps

Introduction | When to Use lss_design() | When to Use Traditional lss() | Simulated Data Setup | Quick Start | Multi-Run Experiments | Onset Convention: Run-Relative | Why Run-Relative Onsets? | Adding Baseline Correction | Adding Motion Parameters | Multi-Basis HRFs | Ridge Regularization | Comparison with design_spec | Using design_spec (old approach) | Using lss_design() (new approach) | Validation: Estimated vs True Betas | Advanced: Parametric Modulators | Troubleshooting | Error: "Y has X rows but sampling_frame expects Y scans" | Error: "event_model and baseline_model have different sampling_frames" | Warning: "High collinearity detected" | Summary | Further Reading

Why HRF Variability Matters | Setup | Simulate Data with Variable HRFs | Experiment parameters | Voxel-specific HRFs | Generate signal and noise | Visualise the design | Standard LSS with Canonical HRF | Estimate Voxel-Specific HRFs | Multi-basis GLM | Apply Voxel-Specific HRFs in LSS | OASIS Alternative | Compare Methods | Compute accuracy metrics | Scatter plots | Next Steps