A POWER ANALYSIS FOR MODEL-X KNOCKOFFS WITH ℓ_p-REGULARIZED STATISTICS

Keyphrases

• Selection Strategy 100%
• Exact Asymptotics 100%
• Approximate Message Passing 100%
• Power Analysis 100%
• Knockoffs 100%
• Regularized Estimator 100%
• Model-X Knockoffs 100%
• Performance Prediction 50%
• No Prior Information 50%
• False Discovery Rate 50%
• Least Absolute Shrinkage and Selection Operator (LASSO) 50%
• Modern Theory 50%
• Receiver Operating Characteristic Curve 50%
• Regression Problem 50%
• Nearly Optimal 50%
• Design Matrix 50%
• Selection Property 50%
• Penalized Likelihood 50%
• I-type 50%
• Type II Error 50%
• Type I Error 50%
• High-dimensional Regression 50%
• PASS Theory 50%
• Augmented Design 50%
• Thresholded Lasso 50%
• Likelihood Estimates 50%
• Type Errors 50%
• Lasso Selection 50%

Mathematics

• Approximates 100%
• Asymptotics 100%
• Power Analysis 100%
• Covariate 50%
• False Discovery Rate 50%
• Design Matrix 50%
• Cross-Validation 50%
• Characteristic Curve 50%
• Type II error 50%
• Central Topic 50%
• Linear Regression Analysis 50%