User guide

TODO: define the target audience of the user guide.

Table of contents

• 1. General concepts
  • 1.1. Definition of concepts
  • 1.2. Statistical guarantees for variable selection
  • 1.3. Generalized Linear Model (GLM) Coefficient
  • 1.4. Generalized Total Sobol Index
• 2. Sparse Linear Models
  • 2.1. Desparsified Lasso
  • 2.2. Model-X Knockoffs
  • 2.3. Distilled Conditional Randomization Test
• 3. Model-agnostic methods
  • 3.1. Conditional Feature Importance
  • 3.2. Permutation Feature Importance
  • 3.3. Leave-One-Covariate-Out
• 4. Marginal methods
  • 4.1. Leave-One-Covariate-In
• 5. Tools for visualization
• 6. Measuring the importance of feature groups
• 7. Inference in high dimension
  • 7.1. Naive inference in high dimension is ill-posed
  • 7.2. Feature Grouping and its shortcomings
  • 7.3. What type of Control does this Ensemble of CLustered inference come with ?
  • 7.4. References